lecture1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Link to notebook: https://tinyurl.com/lecture1sp2020\n",
    "\n",
    "# Pandas and Intro to Project Development\n",
    "\n",
    "February 24, 2020\n",
    "\n",
    "Data Science Society Spring 2020\n",
    "\n",
    "Kevin Chai & Anita Shen\n",
    "\n",
    "Dataset: https://www.kaggle.com/neuromusic/avocado-prices/data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing csv Files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataframe we will be working with today represents weekly 2018 retail scan data for National retail volume (units) and price of avocados.\n",
    "\n",
    "In pandas, we read csv files by using pd.read_csv. We read in our avocado dataframe in the cell below and assign it to the variable avocado. We can also use **df.head()** to display our dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>1.33</td>\n",
       "      <td>64236.62</td>\n",
       "      <td>1036.74</td>\n",
       "      <td>54454.85</td>\n",
       "      <td>48.16</td>\n",
       "      <td>8696.87</td>\n",
       "      <td>8603.62</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-12-20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>54876.98</td>\n",
       "      <td>674.28</td>\n",
       "      <td>44638.81</td>\n",
       "      <td>58.33</td>\n",
       "      <td>9505.56</td>\n",
       "      <td>9408.07</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-12-13</td>\n",
       "      <td>0.93</td>\n",
       "      <td>118220.22</td>\n",
       "      <td>794.70</td>\n",
       "      <td>109149.67</td>\n",
       "      <td>130.50</td>\n",
       "      <td>8145.35</td>\n",
       "      <td>8042.21</td>\n",
       "      <td>103.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-12-06</td>\n",
       "      <td>1.08</td>\n",
       "      <td>78992.15</td>\n",
       "      <td>1132.00</td>\n",
       "      <td>71976.41</td>\n",
       "      <td>72.58</td>\n",
       "      <td>5811.16</td>\n",
       "      <td>5677.40</td>\n",
       "      <td>133.76</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-11-29</td>\n",
       "      <td>1.28</td>\n",
       "      <td>51039.60</td>\n",
       "      <td>941.48</td>\n",
       "      <td>43838.39</td>\n",
       "      <td>75.78</td>\n",
       "      <td>6183.95</td>\n",
       "      <td>5986.26</td>\n",
       "      <td>197.69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0        Date  AveragePrice  Total Volume     4046       4225  \\\n",
       "0           0  2015-12-27          1.33      64236.62  1036.74   54454.85   \n",
       "1           1  2015-12-20          1.35      54876.98   674.28   44638.81   \n",
       "2           2  2015-12-13          0.93     118220.22   794.70  109149.67   \n",
       "3           3  2015-12-06          1.08      78992.15  1132.00   71976.41   \n",
       "4           4  2015-11-29          1.28      51039.60   941.48   43838.39   \n",
       "\n",
       "     4770  Total Bags  Small Bags  Large Bags  XLarge Bags          type  \\\n",
       "0   48.16     8696.87     8603.62       93.25          0.0  conventional   \n",
       "1   58.33     9505.56     9408.07       97.49          0.0  conventional   \n",
       "2  130.50     8145.35     8042.21      103.14          0.0  conventional   \n",
       "3   72.58     5811.16     5677.40      133.76          0.0  conventional   \n",
       "4   75.78     6183.95     5986.26      197.69          0.0  conventional   \n",
       "\n",
       "   year  region  \n",
       "0  2015  Albany  \n",
       "1  2015  Albany  \n",
       "2  2015  Albany  \n",
       "3  2015  Albany  \n",
       "4  2015  Albany  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado = pd.read_csv(\"avocado.csv\")\n",
    "avocado.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Common Functions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. df.head() gets you the first 5 rows of your dataframe\n",
    "2. df.size outputs the number of rows in the dataframe\n",
    "3. df.shape gives you the (row,column) pair of the dataframe\n",
    "4. df.columns describes the dataframe columns\n",
    "5. df.sort_values(\"attribute\") sort by the values of a column\n",
    "6. df.drop[\"column\", axis = 1] removes an entire column from the dataframe. axis=0 removes certain values from a row\n",
    "7. df[\"new column name\"] = array. adds a new column to our dataframe\n",
    "8. df.loc[[index], column name] selects certain values by column names\n",
    "9. df.iloc[[row], [column]] selects single value by row and column\n",
    "10. df.apply(function) applies function to certain series in the dataframe\n",
    "\n",
    "Cheat Sheet: http://datacamp-community-prod.s3.amazonaws.com/dbed353d-2757-4617-8206-8767ab379ab3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Acessing Columns\n",
    "We can access certain columns of our dataframe by using **df[\"column_name\"]** which returns a Series. For example, if we wanted to access the \"Date\" column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2015-12-27\n",
       "1    2015-12-20\n",
       "2    2015-12-13\n",
       "3    2015-12-06\n",
       "4    2015-11-29\n",
       "5    2015-11-22\n",
       "6    2015-11-15\n",
       "7    2015-11-08\n",
       "8    2015-11-01\n",
       "9    2015-10-25\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = avocado[\"Date\"]\n",
    "dates.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Filtering Data\n",
    "To filter our data, we can use **df.loc()**. For example, if we wanted to return a dataframe that did not include the year 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2808</th>\n",
       "      <td>0</td>\n",
       "      <td>2016-12-25</td>\n",
       "      <td>1.52</td>\n",
       "      <td>73341.73</td>\n",
       "      <td>3202.39</td>\n",
       "      <td>58280.33</td>\n",
       "      <td>426.92</td>\n",
       "      <td>11432.09</td>\n",
       "      <td>11017.32</td>\n",
       "      <td>411.83</td>\n",
       "      <td>2.94</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
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       "    <tr>\n",
       "      <th>2809</th>\n",
       "      <td>1</td>\n",
       "      <td>2016-12-18</td>\n",
       "      <td>1.53</td>\n",
       "      <td>68938.53</td>\n",
       "      <td>3345.36</td>\n",
       "      <td>55949.79</td>\n",
       "      <td>138.72</td>\n",
       "      <td>9504.66</td>\n",
       "      <td>8876.65</td>\n",
       "      <td>587.73</td>\n",
       "      <td>40.28</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
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       "    <tr>\n",
       "      <th>2810</th>\n",
       "      <td>2</td>\n",
       "      <td>2016-12-11</td>\n",
       "      <td>1.49</td>\n",
       "      <td>71777.85</td>\n",
       "      <td>2323.39</td>\n",
       "      <td>56545.79</td>\n",
       "      <td>86.65</td>\n",
       "      <td>12822.02</td>\n",
       "      <td>12176.75</td>\n",
       "      <td>645.27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
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       "    <tr>\n",
       "      <th>2811</th>\n",
       "      <td>3</td>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>1.48</td>\n",
       "      <td>113031.96</td>\n",
       "      <td>6530.78</td>\n",
       "      <td>99746.05</td>\n",
       "      <td>50.84</td>\n",
       "      <td>6704.29</td>\n",
       "      <td>6476.12</td>\n",
       "      <td>228.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2812</th>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-27</td>\n",
       "      <td>1.52</td>\n",
       "      <td>58171.89</td>\n",
       "      <td>2793.99</td>\n",
       "      <td>47106.18</td>\n",
       "      <td>18.14</td>\n",
       "      <td>8253.58</td>\n",
       "      <td>7973.98</td>\n",
       "      <td>279.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2813</th>\n",
       "      <td>5</td>\n",
       "      <td>2016-11-20</td>\n",
       "      <td>1.56</td>\n",
       "      <td>70089.51</td>\n",
       "      <td>3675.63</td>\n",
       "      <td>56898.54</td>\n",
       "      <td>11.00</td>\n",
       "      <td>9504.34</td>\n",
       "      <td>9238.40</td>\n",
       "      <td>209.00</td>\n",
       "      <td>56.94</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2814</th>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>1.62</td>\n",
       "      <td>63608.01</td>\n",
       "      <td>3523.63</td>\n",
       "      <td>49837.68</td>\n",
       "      <td>34.00</td>\n",
       "      <td>10212.70</td>\n",
       "      <td>9790.67</td>\n",
       "      <td>422.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
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       "    <tr>\n",
       "      <th>2815</th>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-06</td>\n",
       "      <td>1.63</td>\n",
       "      <td>57178.20</td>\n",
       "      <td>3212.04</td>\n",
       "      <td>43024.32</td>\n",
       "      <td>36.40</td>\n",
       "      <td>10905.44</td>\n",
       "      <td>10474.09</td>\n",
       "      <td>431.35</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
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       "    <tr>\n",
       "      <th>2816</th>\n",
       "      <td>8</td>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>1.46</td>\n",
       "      <td>58375.10</td>\n",
       "      <td>3187.14</td>\n",
       "      <td>45898.52</td>\n",
       "      <td>54.31</td>\n",
       "      <td>9235.13</td>\n",
       "      <td>9153.12</td>\n",
       "      <td>82.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>9</td>\n",
       "      <td>2016-10-23</td>\n",
       "      <td>1.19</td>\n",
       "      <td>92080.35</td>\n",
       "      <td>4222.93</td>\n",
       "      <td>77537.36</td>\n",
       "      <td>46.00</td>\n",
       "      <td>10274.06</td>\n",
       "      <td>10160.26</td>\n",
       "      <td>113.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>10</td>\n",
       "      <td>2016-10-16</td>\n",
       "      <td>1.40</td>\n",
       "      <td>69060.90</td>\n",
       "      <td>4027.42</td>\n",
       "      <td>54186.55</td>\n",
       "      <td>53.77</td>\n",
       "      <td>10793.16</td>\n",
       "      <td>10434.39</td>\n",
       "      <td>358.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2819</th>\n",
       "      <td>11</td>\n",
       "      <td>2016-10-09</td>\n",
       "      <td>1.13</td>\n",
       "      <td>101087.84</td>\n",
       "      <td>3641.46</td>\n",
       "      <td>87174.41</td>\n",
       "      <td>102.15</td>\n",
       "      <td>10169.82</td>\n",
       "      <td>9744.41</td>\n",
       "      <td>425.41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2820</th>\n",
       "      <td>12</td>\n",
       "      <td>2016-10-02</td>\n",
       "      <td>1.51</td>\n",
       "      <td>75480.26</td>\n",
       "      <td>4109.22</td>\n",
       "      <td>57515.76</td>\n",
       "      <td>84.08</td>\n",
       "      <td>13771.20</td>\n",
       "      <td>13345.52</td>\n",
       "      <td>425.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2821</th>\n",
       "      <td>13</td>\n",
       "      <td>2016-09-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>96853.15</td>\n",
       "      <td>7658.55</td>\n",
       "      <td>79425.81</td>\n",
       "      <td>43.25</td>\n",
       "      <td>9725.54</td>\n",
       "      <td>9586.80</td>\n",
       "      <td>138.74</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2822</th>\n",
       "      <td>14</td>\n",
       "      <td>2016-09-18</td>\n",
       "      <td>1.39</td>\n",
       "      <td>79513.63</td>\n",
       "      <td>6624.37</td>\n",
       "      <td>63384.56</td>\n",
       "      <td>37.48</td>\n",
       "      <td>9467.22</td>\n",
       "      <td>8958.14</td>\n",
       "      <td>509.08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2823</th>\n",
       "      <td>15</td>\n",
       "      <td>2016-09-11</td>\n",
       "      <td>1.37</td>\n",
       "      <td>81473.15</td>\n",
       "      <td>6258.88</td>\n",
       "      <td>63511.85</td>\n",
       "      <td>42.26</td>\n",
       "      <td>11660.16</td>\n",
       "      <td>10839.17</td>\n",
       "      <td>815.99</td>\n",
       "      <td>5.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2824</th>\n",
       "      <td>16</td>\n",
       "      <td>2016-09-04</td>\n",
       "      <td>1.44</td>\n",
       "      <td>95456.26</td>\n",
       "      <td>14741.13</td>\n",
       "      <td>64966.75</td>\n",
       "      <td>88.11</td>\n",
       "      <td>15660.27</td>\n",
       "      <td>15340.19</td>\n",
       "      <td>220.08</td>\n",
       "      <td>100.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2825</th>\n",
       "      <td>17</td>\n",
       "      <td>2016-08-28</td>\n",
       "      <td>1.18</td>\n",
       "      <td>145323.22</td>\n",
       "      <td>34912.97</td>\n",
       "      <td>94928.79</td>\n",
       "      <td>53.85</td>\n",
       "      <td>15427.61</td>\n",
       "      <td>14367.64</td>\n",
       "      <td>269.97</td>\n",
       "      <td>790.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2826</th>\n",
       "      <td>18</td>\n",
       "      <td>2016-08-21</td>\n",
       "      <td>1.43</td>\n",
       "      <td>94882.79</td>\n",
       "      <td>14520.36</td>\n",
       "      <td>63416.88</td>\n",
       "      <td>28.03</td>\n",
       "      <td>16917.52</td>\n",
       "      <td>15811.00</td>\n",
       "      <td>286.52</td>\n",
       "      <td>820.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2827</th>\n",
       "      <td>19</td>\n",
       "      <td>2016-08-14</td>\n",
       "      <td>1.20</td>\n",
       "      <td>110528.09</td>\n",
       "      <td>24000.62</td>\n",
       "      <td>72970.23</td>\n",
       "      <td>26.76</td>\n",
       "      <td>13530.48</td>\n",
       "      <td>12434.82</td>\n",
       "      <td>350.10</td>\n",
       "      <td>745.56</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2828</th>\n",
       "      <td>20</td>\n",
       "      <td>2016-08-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>99683.11</td>\n",
       "      <td>14670.87</td>\n",
       "      <td>69054.28</td>\n",
       "      <td>10.90</td>\n",
       "      <td>15947.06</td>\n",
       "      <td>14597.20</td>\n",
       "      <td>178.19</td>\n",
       "      <td>1171.67</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2829</th>\n",
       "      <td>21</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1.61</td>\n",
       "      <td>125586.57</td>\n",
       "      <td>9293.65</td>\n",
       "      <td>96915.41</td>\n",
       "      <td>25.46</td>\n",
       "      <td>19352.05</td>\n",
       "      <td>18803.23</td>\n",
       "      <td>78.82</td>\n",
       "      <td>470.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2830</th>\n",
       "      <td>22</td>\n",
       "      <td>2016-07-24</td>\n",
       "      <td>1.46</td>\n",
       "      <td>98321.14</td>\n",
       "      <td>11580.64</td>\n",
       "      <td>65195.63</td>\n",
       "      <td>13.73</td>\n",
       "      <td>21531.14</td>\n",
       "      <td>18639.29</td>\n",
       "      <td>241.85</td>\n",
       "      <td>2650.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2831</th>\n",
       "      <td>23</td>\n",
       "      <td>2016-07-17</td>\n",
       "      <td>1.31</td>\n",
       "      <td>89228.02</td>\n",
       "      <td>9273.69</td>\n",
       "      <td>64260.69</td>\n",
       "      <td>80.07</td>\n",
       "      <td>15613.57</td>\n",
       "      <td>13439.76</td>\n",
       "      <td>688.81</td>\n",
       "      <td>1485.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2832</th>\n",
       "      <td>24</td>\n",
       "      <td>2016-07-10</td>\n",
       "      <td>1.11</td>\n",
       "      <td>131630.13</td>\n",
       "      <td>20970.24</td>\n",
       "      <td>96581.82</td>\n",
       "      <td>46.49</td>\n",
       "      <td>14031.58</td>\n",
       "      <td>10876.00</td>\n",
       "      <td>470.58</td>\n",
       "      <td>2685.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2833</th>\n",
       "      <td>25</td>\n",
       "      <td>2016-07-03</td>\n",
       "      <td>1.42</td>\n",
       "      <td>115907.61</td>\n",
       "      <td>8373.77</td>\n",
       "      <td>82122.04</td>\n",
       "      <td>146.83</td>\n",
       "      <td>25264.97</td>\n",
       "      <td>21872.64</td>\n",
       "      <td>492.33</td>\n",
       "      <td>2900.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2834</th>\n",
       "      <td>26</td>\n",
       "      <td>2016-06-26</td>\n",
       "      <td>1.50</td>\n",
       "      <td>133086.66</td>\n",
       "      <td>7923.01</td>\n",
       "      <td>106656.84</td>\n",
       "      <td>37.42</td>\n",
       "      <td>18469.39</td>\n",
       "      <td>16479.75</td>\n",
       "      <td>419.64</td>\n",
       "      <td>1570.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2835</th>\n",
       "      <td>27</td>\n",
       "      <td>2016-06-19</td>\n",
       "      <td>1.42</td>\n",
       "      <td>112817.51</td>\n",
       "      <td>6766.63</td>\n",
       "      <td>85374.27</td>\n",
       "      <td>30.07</td>\n",
       "      <td>20646.54</td>\n",
       "      <td>18526.59</td>\n",
       "      <td>389.95</td>\n",
       "      <td>1730.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2836</th>\n",
       "      <td>28</td>\n",
       "      <td>2016-06-12</td>\n",
       "      <td>1.38</td>\n",
       "      <td>111394.50</td>\n",
       "      <td>7531.24</td>\n",
       "      <td>83771.34</td>\n",
       "      <td>81.25</td>\n",
       "      <td>20010.67</td>\n",
       "      <td>18368.49</td>\n",
       "      <td>282.18</td>\n",
       "      <td>1360.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2837</th>\n",
       "      <td>29</td>\n",
       "      <td>2016-06-05</td>\n",
       "      <td>1.47</td>\n",
       "      <td>115857.12</td>\n",
       "      <td>4288.46</td>\n",
       "      <td>92055.75</td>\n",
       "      <td>53.98</td>\n",
       "      <td>19458.93</td>\n",
       "      <td>17385.60</td>\n",
       "      <td>398.33</td>\n",
       "      <td>1675.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18219</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1317000.47</td>\n",
       "      <td>98465.26</td>\n",
       "      <td>270798.27</td>\n",
       "      <td>1839.80</td>\n",
       "      <td>945638.02</td>\n",
       "      <td>768242.42</td>\n",
       "      <td>177144.00</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18220</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1384683.41</td>\n",
       "      <td>117922.52</td>\n",
       "      <td>287724.61</td>\n",
       "      <td>1703.52</td>\n",
       "      <td>977084.84</td>\n",
       "      <td>774695.74</td>\n",
       "      <td>201878.69</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18221</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.61</td>\n",
       "      <td>1336979.09</td>\n",
       "      <td>118616.17</td>\n",
       "      <td>280080.34</td>\n",
       "      <td>1270.61</td>\n",
       "      <td>936859.49</td>\n",
       "      <td>796104.27</td>\n",
       "      <td>140652.84</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18222</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1283987.65</td>\n",
       "      <td>108705.28</td>\n",
       "      <td>259172.13</td>\n",
       "      <td>1490.02</td>\n",
       "      <td>914409.26</td>\n",
       "      <td>710654.40</td>\n",
       "      <td>203526.59</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18223</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.59</td>\n",
       "      <td>1476651.08</td>\n",
       "      <td>145680.62</td>\n",
       "      <td>323669.83</td>\n",
       "      <td>1580.01</td>\n",
       "      <td>1005593.78</td>\n",
       "      <td>858772.69</td>\n",
       "      <td>146808.97</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18224</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1517332.70</td>\n",
       "      <td>129541.43</td>\n",
       "      <td>296490.29</td>\n",
       "      <td>1289.07</td>\n",
       "      <td>1089861.24</td>\n",
       "      <td>915452.78</td>\n",
       "      <td>174381.57</td>\n",
       "      <td>26.89</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18225</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.60</td>\n",
       "      <td>271723.08</td>\n",
       "      <td>26996.28</td>\n",
       "      <td>77861.39</td>\n",
       "      <td>117.56</td>\n",
       "      <td>166747.85</td>\n",
       "      <td>87108.00</td>\n",
       "      <td>79495.39</td>\n",
       "      <td>144.46</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18226</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.73</td>\n",
       "      <td>210067.47</td>\n",
       "      <td>33437.98</td>\n",
       "      <td>47165.54</td>\n",
       "      <td>110.40</td>\n",
       "      <td>129353.55</td>\n",
       "      <td>73163.12</td>\n",
       "      <td>56020.24</td>\n",
       "      <td>170.19</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18227</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.63</td>\n",
       "      <td>264691.87</td>\n",
       "      <td>27566.25</td>\n",
       "      <td>60383.57</td>\n",
       "      <td>276.42</td>\n",
       "      <td>176465.63</td>\n",
       "      <td>107174.93</td>\n",
       "      <td>69290.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18228</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.46</td>\n",
       "      <td>347373.17</td>\n",
       "      <td>25990.60</td>\n",
       "      <td>71213.19</td>\n",
       "      <td>79.01</td>\n",
       "      <td>250090.37</td>\n",
       "      <td>85835.17</td>\n",
       "      <td>164087.33</td>\n",
       "      <td>167.87</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18229</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.49</td>\n",
       "      <td>301985.61</td>\n",
       "      <td>34200.18</td>\n",
       "      <td>49139.34</td>\n",
       "      <td>85.58</td>\n",
       "      <td>218560.51</td>\n",
       "      <td>99989.62</td>\n",
       "      <td>118314.77</td>\n",
       "      <td>256.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18230</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.64</td>\n",
       "      <td>224798.60</td>\n",
       "      <td>30149.00</td>\n",
       "      <td>38800.64</td>\n",
       "      <td>123.13</td>\n",
       "      <td>155725.83</td>\n",
       "      <td>120428.13</td>\n",
       "      <td>35257.73</td>\n",
       "      <td>39.97</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18231</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.47</td>\n",
       "      <td>275248.53</td>\n",
       "      <td>24732.55</td>\n",
       "      <td>61713.53</td>\n",
       "      <td>243.00</td>\n",
       "      <td>188559.45</td>\n",
       "      <td>88497.05</td>\n",
       "      <td>99810.80</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18232</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.41</td>\n",
       "      <td>283378.47</td>\n",
       "      <td>22474.66</td>\n",
       "      <td>55360.49</td>\n",
       "      <td>133.41</td>\n",
       "      <td>205409.91</td>\n",
       "      <td>70232.59</td>\n",
       "      <td>134666.91</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18233</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.80</td>\n",
       "      <td>185974.53</td>\n",
       "      <td>22918.40</td>\n",
       "      <td>33051.14</td>\n",
       "      <td>93.52</td>\n",
       "      <td>129911.47</td>\n",
       "      <td>77822.23</td>\n",
       "      <td>51986.86</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18234</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.83</td>\n",
       "      <td>189317.99</td>\n",
       "      <td>27049.44</td>\n",
       "      <td>33561.32</td>\n",
       "      <td>439.47</td>\n",
       "      <td>128267.76</td>\n",
       "      <td>76091.99</td>\n",
       "      <td>51947.50</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18235</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.82</td>\n",
       "      <td>207999.67</td>\n",
       "      <td>33869.12</td>\n",
       "      <td>47435.14</td>\n",
       "      <td>433.52</td>\n",
       "      <td>126261.89</td>\n",
       "      <td>89115.78</td>\n",
       "      <td>37133.99</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18236</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>297190.60</td>\n",
       "      <td>34734.97</td>\n",
       "      <td>62967.74</td>\n",
       "      <td>157.77</td>\n",
       "      <td>199330.12</td>\n",
       "      <td>103761.55</td>\n",
       "      <td>95544.39</td>\n",
       "      <td>24.18</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18237</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>15303.40</td>\n",
       "      <td>2325.30</td>\n",
       "      <td>2171.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10806.44</td>\n",
       "      <td>10569.80</td>\n",
       "      <td>236.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18238</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>15896.38</td>\n",
       "      <td>2055.35</td>\n",
       "      <td>1499.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12341.48</td>\n",
       "      <td>12114.81</td>\n",
       "      <td>226.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18239</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>22128.42</td>\n",
       "      <td>2162.67</td>\n",
       "      <td>3194.25</td>\n",
       "      <td>8.93</td>\n",
       "      <td>16762.57</td>\n",
       "      <td>16510.32</td>\n",
       "      <td>252.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18240</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.54</td>\n",
       "      <td>17393.30</td>\n",
       "      <td>1832.24</td>\n",
       "      <td>1905.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13655.49</td>\n",
       "      <td>13401.93</td>\n",
       "      <td>253.56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18241</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.57</td>\n",
       "      <td>18421.24</td>\n",
       "      <td>1974.26</td>\n",
       "      <td>2482.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13964.33</td>\n",
       "      <td>13698.27</td>\n",
       "      <td>266.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18242</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>17597.12</td>\n",
       "      <td>1892.05</td>\n",
       "      <td>1928.36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13776.71</td>\n",
       "      <td>13553.53</td>\n",
       "      <td>223.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18243</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.57</td>\n",
       "      <td>15986.17</td>\n",
       "      <td>1924.28</td>\n",
       "      <td>1368.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12693.57</td>\n",
       "      <td>12437.35</td>\n",
       "      <td>256.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18244</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.63</td>\n",
       "      <td>17074.83</td>\n",
       "      <td>2046.96</td>\n",
       "      <td>1529.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13498.67</td>\n",
       "      <td>13066.82</td>\n",
       "      <td>431.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18245</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.71</td>\n",
       "      <td>13888.04</td>\n",
       "      <td>1191.70</td>\n",
       "      <td>3431.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9264.84</td>\n",
       "      <td>8940.04</td>\n",
       "      <td>324.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.87</td>\n",
       "      <td>13766.76</td>\n",
       "      <td>1191.92</td>\n",
       "      <td>2452.79</td>\n",
       "      <td>727.94</td>\n",
       "      <td>9394.11</td>\n",
       "      <td>9351.80</td>\n",
       "      <td>42.31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18247</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.93</td>\n",
       "      <td>16205.22</td>\n",
       "      <td>1527.63</td>\n",
       "      <td>2981.04</td>\n",
       "      <td>727.01</td>\n",
       "      <td>10969.54</td>\n",
       "      <td>10919.54</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18248</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.62</td>\n",
       "      <td>17489.58</td>\n",
       "      <td>2894.77</td>\n",
       "      <td>2356.13</td>\n",
       "      <td>224.53</td>\n",
       "      <td>12014.15</td>\n",
       "      <td>11988.14</td>\n",
       "      <td>26.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12634 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0        Date  AveragePrice  Total Volume       4046  \\\n",
       "2808            0  2016-12-25          1.52      73341.73    3202.39   \n",
       "2809            1  2016-12-18          1.53      68938.53    3345.36   \n",
       "2810            2  2016-12-11          1.49      71777.85    2323.39   \n",
       "2811            3  2016-12-04          1.48     113031.96    6530.78   \n",
       "2812            4  2016-11-27          1.52      58171.89    2793.99   \n",
       "2813            5  2016-11-20          1.56      70089.51    3675.63   \n",
       "2814            6  2016-11-13          1.62      63608.01    3523.63   \n",
       "2815            7  2016-11-06          1.63      57178.20    3212.04   \n",
       "2816            8  2016-10-30          1.46      58375.10    3187.14   \n",
       "2817            9  2016-10-23          1.19      92080.35    4222.93   \n",
       "2818           10  2016-10-16          1.40      69060.90    4027.42   \n",
       "2819           11  2016-10-09          1.13     101087.84    3641.46   \n",
       "2820           12  2016-10-02          1.51      75480.26    4109.22   \n",
       "2821           13  2016-09-25          1.62      96853.15    7658.55   \n",
       "2822           14  2016-09-18          1.39      79513.63    6624.37   \n",
       "2823           15  2016-09-11          1.37      81473.15    6258.88   \n",
       "2824           16  2016-09-04          1.44      95456.26   14741.13   \n",
       "2825           17  2016-08-28          1.18     145323.22   34912.97   \n",
       "2826           18  2016-08-21          1.43      94882.79   14520.36   \n",
       "2827           19  2016-08-14          1.20     110528.09   24000.62   \n",
       "2828           20  2016-08-07          1.48      99683.11   14670.87   \n",
       "2829           21  2016-07-31          1.61     125586.57    9293.65   \n",
       "2830           22  2016-07-24          1.46      98321.14   11580.64   \n",
       "2831           23  2016-07-17          1.31      89228.02    9273.69   \n",
       "2832           24  2016-07-10          1.11     131630.13   20970.24   \n",
       "2833           25  2016-07-03          1.42     115907.61    8373.77   \n",
       "2834           26  2016-06-26          1.50     133086.66    7923.01   \n",
       "2835           27  2016-06-19          1.42     112817.51    6766.63   \n",
       "2836           28  2016-06-12          1.38     111394.50    7531.24   \n",
       "2837           29  2016-06-05          1.47     115857.12    4288.46   \n",
       "...           ...         ...           ...           ...        ...   \n",
       "18219           6  2018-02-11          1.56    1317000.47   98465.26   \n",
       "18220           7  2018-02-04          1.53    1384683.41  117922.52   \n",
       "18221           8  2018-01-28          1.61    1336979.09  118616.17   \n",
       "18222           9  2018-01-21          1.63    1283987.65  108705.28   \n",
       "18223          10  2018-01-14          1.59    1476651.08  145680.62   \n",
       "18224          11  2018-01-07          1.51    1517332.70  129541.43   \n",
       "18225           0  2018-03-25          1.60     271723.08   26996.28   \n",
       "18226           1  2018-03-18          1.73     210067.47   33437.98   \n",
       "18227           2  2018-03-11          1.63     264691.87   27566.25   \n",
       "18228           3  2018-03-04          1.46     347373.17   25990.60   \n",
       "18229           4  2018-02-25          1.49     301985.61   34200.18   \n",
       "18230           5  2018-02-18          1.64     224798.60   30149.00   \n",
       "18231           6  2018-02-11          1.47     275248.53   24732.55   \n",
       "18232           7  2018-02-04          1.41     283378.47   22474.66   \n",
       "18233           8  2018-01-28          1.80     185974.53   22918.40   \n",
       "18234           9  2018-01-21          1.83     189317.99   27049.44   \n",
       "18235          10  2018-01-14          1.82     207999.67   33869.12   \n",
       "18236          11  2018-01-07          1.48     297190.60   34734.97   \n",
       "18237           0  2018-03-25          1.62      15303.40    2325.30   \n",
       "18238           1  2018-03-18          1.56      15896.38    2055.35   \n",
       "18239           2  2018-03-11          1.56      22128.42    2162.67   \n",
       "18240           3  2018-03-04          1.54      17393.30    1832.24   \n",
       "18241           4  2018-02-25          1.57      18421.24    1974.26   \n",
       "18242           5  2018-02-18          1.56      17597.12    1892.05   \n",
       "18243           6  2018-02-11          1.57      15986.17    1924.28   \n",
       "18244           7  2018-02-04          1.63      17074.83    2046.96   \n",
       "18245           8  2018-01-28          1.71      13888.04    1191.70   \n",
       "18246           9  2018-01-21          1.87      13766.76    1191.92   \n",
       "18247          10  2018-01-14          1.93      16205.22    1527.63   \n",
       "18248          11  2018-01-07          1.62      17489.58    2894.77   \n",
       "\n",
       "            4225     4770  Total Bags  Small Bags  Large Bags  XLarge Bags  \\\n",
       "2808    58280.33   426.92    11432.09    11017.32      411.83         2.94   \n",
       "2809    55949.79   138.72     9504.66     8876.65      587.73        40.28   \n",
       "2810    56545.79    86.65    12822.02    12176.75      645.27         0.00   \n",
       "2811    99746.05    50.84     6704.29     6476.12      228.17         0.00   \n",
       "2812    47106.18    18.14     8253.58     7973.98      279.60         0.00   \n",
       "2813    56898.54    11.00     9504.34     9238.40      209.00        56.94   \n",
       "2814    49837.68    34.00    10212.70     9790.67      422.03         0.00   \n",
       "2815    43024.32    36.40    10905.44    10474.09      431.35         0.00   \n",
       "2816    45898.52    54.31     9235.13     9153.12       82.01         0.00   \n",
       "2817    77537.36    46.00    10274.06    10160.26      113.80         0.00   \n",
       "2818    54186.55    53.77    10793.16    10434.39      358.77         0.00   \n",
       "2819    87174.41   102.15    10169.82     9744.41      425.41         0.00   \n",
       "2820    57515.76    84.08    13771.20    13345.52      425.68         0.00   \n",
       "2821    79425.81    43.25     9725.54     9586.80      138.74         0.00   \n",
       "2822    63384.56    37.48     9467.22     8958.14      509.08         0.00   \n",
       "2823    63511.85    42.26    11660.16    10839.17      815.99         5.00   \n",
       "2824    64966.75    88.11    15660.27    15340.19      220.08       100.00   \n",
       "2825    94928.79    53.85    15427.61    14367.64      269.97       790.00   \n",
       "2826    63416.88    28.03    16917.52    15811.00      286.52       820.00   \n",
       "2827    72970.23    26.76    13530.48    12434.82      350.10       745.56   \n",
       "2828    69054.28    10.90    15947.06    14597.20      178.19      1171.67   \n",
       "2829    96915.41    25.46    19352.05    18803.23       78.82       470.00   \n",
       "2830    65195.63    13.73    21531.14    18639.29      241.85      2650.00   \n",
       "2831    64260.69    80.07    15613.57    13439.76      688.81      1485.00   \n",
       "2832    96581.82    46.49    14031.58    10876.00      470.58      2685.00   \n",
       "2833    82122.04   146.83    25264.97    21872.64      492.33      2900.00   \n",
       "2834   106656.84    37.42    18469.39    16479.75      419.64      1570.00   \n",
       "2835    85374.27    30.07    20646.54    18526.59      389.95      1730.00   \n",
       "2836    83771.34    81.25    20010.67    18368.49      282.18      1360.00   \n",
       "2837    92055.75    53.98    19458.93    17385.60      398.33      1675.00   \n",
       "...          ...      ...         ...         ...         ...          ...   \n",
       "18219  270798.27  1839.80   945638.02   768242.42   177144.00       251.60   \n",
       "18220  287724.61  1703.52   977084.84   774695.74   201878.69       510.41   \n",
       "18221  280080.34  1270.61   936859.49   796104.27   140652.84       102.38   \n",
       "18222  259172.13  1490.02   914409.26   710654.40   203526.59       228.27   \n",
       "18223  323669.83  1580.01  1005593.78   858772.69   146808.97        12.12   \n",
       "18224  296490.29  1289.07  1089861.24   915452.78   174381.57        26.89   \n",
       "18225   77861.39   117.56   166747.85    87108.00    79495.39       144.46   \n",
       "18226   47165.54   110.40   129353.55    73163.12    56020.24       170.19   \n",
       "18227   60383.57   276.42   176465.63   107174.93    69290.70         0.00   \n",
       "18228   71213.19    79.01   250090.37    85835.17   164087.33       167.87   \n",
       "18229   49139.34    85.58   218560.51    99989.62   118314.77       256.12   \n",
       "18230   38800.64   123.13   155725.83   120428.13    35257.73        39.97   \n",
       "18231   61713.53   243.00   188559.45    88497.05    99810.80       251.60   \n",
       "18232   55360.49   133.41   205409.91    70232.59   134666.91       510.41   \n",
       "18233   33051.14    93.52   129911.47    77822.23    51986.86       102.38   \n",
       "18234   33561.32   439.47   128267.76    76091.99    51947.50       228.27   \n",
       "18235   47435.14   433.52   126261.89    89115.78    37133.99        12.12   \n",
       "18236   62967.74   157.77   199330.12   103761.55    95544.39        24.18   \n",
       "18237    2171.66     0.00    10806.44    10569.80      236.64         0.00   \n",
       "18238    1499.55     0.00    12341.48    12114.81      226.67         0.00   \n",
       "18239    3194.25     8.93    16762.57    16510.32      252.25         0.00   \n",
       "18240    1905.57     0.00    13655.49    13401.93      253.56         0.00   \n",
       "18241    2482.65     0.00    13964.33    13698.27      266.06         0.00   \n",
       "18242    1928.36     0.00    13776.71    13553.53      223.18         0.00   \n",
       "18243    1368.32     0.00    12693.57    12437.35      256.22         0.00   \n",
       "18244    1529.20     0.00    13498.67    13066.82      431.85         0.00   \n",
       "18245    3431.50     0.00     9264.84     8940.04      324.80         0.00   \n",
       "18246    2452.79   727.94     9394.11     9351.80       42.31         0.00   \n",
       "18247    2981.04   727.01    10969.54    10919.54       50.00         0.00   \n",
       "18248    2356.13   224.53    12014.15    11988.14       26.01         0.00   \n",
       "\n",
       "               type  year            region  \n",
       "2808   conventional  2016            Albany  \n",
       "2809   conventional  2016            Albany  \n",
       "2810   conventional  2016            Albany  \n",
       "2811   conventional  2016            Albany  \n",
       "2812   conventional  2016            Albany  \n",
       "2813   conventional  2016            Albany  \n",
       "2814   conventional  2016            Albany  \n",
       "2815   conventional  2016            Albany  \n",
       "2816   conventional  2016            Albany  \n",
       "2817   conventional  2016            Albany  \n",
       "2818   conventional  2016            Albany  \n",
       "2819   conventional  2016            Albany  \n",
       "2820   conventional  2016            Albany  \n",
       "2821   conventional  2016            Albany  \n",
       "2822   conventional  2016            Albany  \n",
       "2823   conventional  2016            Albany  \n",
       "2824   conventional  2016            Albany  \n",
       "2825   conventional  2016            Albany  \n",
       "2826   conventional  2016            Albany  \n",
       "2827   conventional  2016            Albany  \n",
       "2828   conventional  2016            Albany  \n",
       "2829   conventional  2016            Albany  \n",
       "2830   conventional  2016            Albany  \n",
       "2831   conventional  2016            Albany  \n",
       "2832   conventional  2016            Albany  \n",
       "2833   conventional  2016            Albany  \n",
       "2834   conventional  2016            Albany  \n",
       "2835   conventional  2016            Albany  \n",
       "2836   conventional  2016            Albany  \n",
       "2837   conventional  2016            Albany  \n",
       "...             ...   ...               ...  \n",
       "18219       organic  2018           TotalUS  \n",
       "18220       organic  2018           TotalUS  \n",
       "18221       organic  2018           TotalUS  \n",
       "18222       organic  2018           TotalUS  \n",
       "18223       organic  2018           TotalUS  \n",
       "18224       organic  2018           TotalUS  \n",
       "18225       organic  2018              West  \n",
       "18226       organic  2018              West  \n",
       "18227       organic  2018              West  \n",
       "18228       organic  2018              West  \n",
       "18229       organic  2018              West  \n",
       "18230       organic  2018              West  \n",
       "18231       organic  2018              West  \n",
       "18232       organic  2018              West  \n",
       "18233       organic  2018              West  \n",
       "18234       organic  2018              West  \n",
       "18235       organic  2018              West  \n",
       "18236       organic  2018              West  \n",
       "18237       organic  2018  WestTexNewMexico  \n",
       "18238       organic  2018  WestTexNewMexico  \n",
       "18239       organic  2018  WestTexNewMexico  \n",
       "18240       organic  2018  WestTexNewMexico  \n",
       "18241       organic  2018  WestTexNewMexico  \n",
       "18242       organic  2018  WestTexNewMexico  \n",
       "18243       organic  2018  WestTexNewMexico  \n",
       "18244       organic  2018  WestTexNewMexico  \n",
       "18245       organic  2018  WestTexNewMexico  \n",
       "18246       organic  2018  WestTexNewMexico  \n",
       "18247       organic  2018  WestTexNewMexico  \n",
       "18248       organic  2018  WestTexNewMexico  \n",
       "\n",
       "[12634 rows x 14 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_2015 = avocado.loc[avocado[\"year\"] != 2015]\n",
    "no_2015"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also have filter with multiple conditions using **df.loc()**. For example if we wanted the exclude the year 2015 and organic avocados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2808</th>\n",
       "      <td>0</td>\n",
       "      <td>2016-12-25</td>\n",
       "      <td>1.52</td>\n",
       "      <td>73341.73</td>\n",
       "      <td>3202.39</td>\n",
       "      <td>58280.33</td>\n",
       "      <td>426.92</td>\n",
       "      <td>11432.09</td>\n",
       "      <td>11017.32</td>\n",
       "      <td>411.83</td>\n",
       "      <td>2.94</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2809</th>\n",
       "      <td>1</td>\n",
       "      <td>2016-12-18</td>\n",
       "      <td>1.53</td>\n",
       "      <td>68938.53</td>\n",
       "      <td>3345.36</td>\n",
       "      <td>55949.79</td>\n",
       "      <td>138.72</td>\n",
       "      <td>9504.66</td>\n",
       "      <td>8876.65</td>\n",
       "      <td>587.73</td>\n",
       "      <td>40.28</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2810</th>\n",
       "      <td>2</td>\n",
       "      <td>2016-12-11</td>\n",
       "      <td>1.49</td>\n",
       "      <td>71777.85</td>\n",
       "      <td>2323.39</td>\n",
       "      <td>56545.79</td>\n",
       "      <td>86.65</td>\n",
       "      <td>12822.02</td>\n",
       "      <td>12176.75</td>\n",
       "      <td>645.27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2811</th>\n",
       "      <td>3</td>\n",
       "      <td>2016-12-04</td>\n",
       "      <td>1.48</td>\n",
       "      <td>113031.96</td>\n",
       "      <td>6530.78</td>\n",
       "      <td>99746.05</td>\n",
       "      <td>50.84</td>\n",
       "      <td>6704.29</td>\n",
       "      <td>6476.12</td>\n",
       "      <td>228.17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2812</th>\n",
       "      <td>4</td>\n",
       "      <td>2016-11-27</td>\n",
       "      <td>1.52</td>\n",
       "      <td>58171.89</td>\n",
       "      <td>2793.99</td>\n",
       "      <td>47106.18</td>\n",
       "      <td>18.14</td>\n",
       "      <td>8253.58</td>\n",
       "      <td>7973.98</td>\n",
       "      <td>279.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2813</th>\n",
       "      <td>5</td>\n",
       "      <td>2016-11-20</td>\n",
       "      <td>1.56</td>\n",
       "      <td>70089.51</td>\n",
       "      <td>3675.63</td>\n",
       "      <td>56898.54</td>\n",
       "      <td>11.00</td>\n",
       "      <td>9504.34</td>\n",
       "      <td>9238.40</td>\n",
       "      <td>209.00</td>\n",
       "      <td>56.94</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2814</th>\n",
       "      <td>6</td>\n",
       "      <td>2016-11-13</td>\n",
       "      <td>1.62</td>\n",
       "      <td>63608.01</td>\n",
       "      <td>3523.63</td>\n",
       "      <td>49837.68</td>\n",
       "      <td>34.00</td>\n",
       "      <td>10212.70</td>\n",
       "      <td>9790.67</td>\n",
       "      <td>422.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2815</th>\n",
       "      <td>7</td>\n",
       "      <td>2016-11-06</td>\n",
       "      <td>1.63</td>\n",
       "      <td>57178.20</td>\n",
       "      <td>3212.04</td>\n",
       "      <td>43024.32</td>\n",
       "      <td>36.40</td>\n",
       "      <td>10905.44</td>\n",
       "      <td>10474.09</td>\n",
       "      <td>431.35</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2816</th>\n",
       "      <td>8</td>\n",
       "      <td>2016-10-30</td>\n",
       "      <td>1.46</td>\n",
       "      <td>58375.10</td>\n",
       "      <td>3187.14</td>\n",
       "      <td>45898.52</td>\n",
       "      <td>54.31</td>\n",
       "      <td>9235.13</td>\n",
       "      <td>9153.12</td>\n",
       "      <td>82.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>9</td>\n",
       "      <td>2016-10-23</td>\n",
       "      <td>1.19</td>\n",
       "      <td>92080.35</td>\n",
       "      <td>4222.93</td>\n",
       "      <td>77537.36</td>\n",
       "      <td>46.00</td>\n",
       "      <td>10274.06</td>\n",
       "      <td>10160.26</td>\n",
       "      <td>113.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>10</td>\n",
       "      <td>2016-10-16</td>\n",
       "      <td>1.40</td>\n",
       "      <td>69060.90</td>\n",
       "      <td>4027.42</td>\n",
       "      <td>54186.55</td>\n",
       "      <td>53.77</td>\n",
       "      <td>10793.16</td>\n",
       "      <td>10434.39</td>\n",
       "      <td>358.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2819</th>\n",
       "      <td>11</td>\n",
       "      <td>2016-10-09</td>\n",
       "      <td>1.13</td>\n",
       "      <td>101087.84</td>\n",
       "      <td>3641.46</td>\n",
       "      <td>87174.41</td>\n",
       "      <td>102.15</td>\n",
       "      <td>10169.82</td>\n",
       "      <td>9744.41</td>\n",
       "      <td>425.41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2820</th>\n",
       "      <td>12</td>\n",
       "      <td>2016-10-02</td>\n",
       "      <td>1.51</td>\n",
       "      <td>75480.26</td>\n",
       "      <td>4109.22</td>\n",
       "      <td>57515.76</td>\n",
       "      <td>84.08</td>\n",
       "      <td>13771.20</td>\n",
       "      <td>13345.52</td>\n",
       "      <td>425.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2821</th>\n",
       "      <td>13</td>\n",
       "      <td>2016-09-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>96853.15</td>\n",
       "      <td>7658.55</td>\n",
       "      <td>79425.81</td>\n",
       "      <td>43.25</td>\n",
       "      <td>9725.54</td>\n",
       "      <td>9586.80</td>\n",
       "      <td>138.74</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2822</th>\n",
       "      <td>14</td>\n",
       "      <td>2016-09-18</td>\n",
       "      <td>1.39</td>\n",
       "      <td>79513.63</td>\n",
       "      <td>6624.37</td>\n",
       "      <td>63384.56</td>\n",
       "      <td>37.48</td>\n",
       "      <td>9467.22</td>\n",
       "      <td>8958.14</td>\n",
       "      <td>509.08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2823</th>\n",
       "      <td>15</td>\n",
       "      <td>2016-09-11</td>\n",
       "      <td>1.37</td>\n",
       "      <td>81473.15</td>\n",
       "      <td>6258.88</td>\n",
       "      <td>63511.85</td>\n",
       "      <td>42.26</td>\n",
       "      <td>11660.16</td>\n",
       "      <td>10839.17</td>\n",
       "      <td>815.99</td>\n",
       "      <td>5.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2824</th>\n",
       "      <td>16</td>\n",
       "      <td>2016-09-04</td>\n",
       "      <td>1.44</td>\n",
       "      <td>95456.26</td>\n",
       "      <td>14741.13</td>\n",
       "      <td>64966.75</td>\n",
       "      <td>88.11</td>\n",
       "      <td>15660.27</td>\n",
       "      <td>15340.19</td>\n",
       "      <td>220.08</td>\n",
       "      <td>100.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2825</th>\n",
       "      <td>17</td>\n",
       "      <td>2016-08-28</td>\n",
       "      <td>1.18</td>\n",
       "      <td>145323.22</td>\n",
       "      <td>34912.97</td>\n",
       "      <td>94928.79</td>\n",
       "      <td>53.85</td>\n",
       "      <td>15427.61</td>\n",
       "      <td>14367.64</td>\n",
       "      <td>269.97</td>\n",
       "      <td>790.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2826</th>\n",
       "      <td>18</td>\n",
       "      <td>2016-08-21</td>\n",
       "      <td>1.43</td>\n",
       "      <td>94882.79</td>\n",
       "      <td>14520.36</td>\n",
       "      <td>63416.88</td>\n",
       "      <td>28.03</td>\n",
       "      <td>16917.52</td>\n",
       "      <td>15811.00</td>\n",
       "      <td>286.52</td>\n",
       "      <td>820.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2827</th>\n",
       "      <td>19</td>\n",
       "      <td>2016-08-14</td>\n",
       "      <td>1.20</td>\n",
       "      <td>110528.09</td>\n",
       "      <td>24000.62</td>\n",
       "      <td>72970.23</td>\n",
       "      <td>26.76</td>\n",
       "      <td>13530.48</td>\n",
       "      <td>12434.82</td>\n",
       "      <td>350.10</td>\n",
       "      <td>745.56</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2828</th>\n",
       "      <td>20</td>\n",
       "      <td>2016-08-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>99683.11</td>\n",
       "      <td>14670.87</td>\n",
       "      <td>69054.28</td>\n",
       "      <td>10.90</td>\n",
       "      <td>15947.06</td>\n",
       "      <td>14597.20</td>\n",
       "      <td>178.19</td>\n",
       "      <td>1171.67</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2829</th>\n",
       "      <td>21</td>\n",
       "      <td>2016-07-31</td>\n",
       "      <td>1.61</td>\n",
       "      <td>125586.57</td>\n",
       "      <td>9293.65</td>\n",
       "      <td>96915.41</td>\n",
       "      <td>25.46</td>\n",
       "      <td>19352.05</td>\n",
       "      <td>18803.23</td>\n",
       "      <td>78.82</td>\n",
       "      <td>470.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2830</th>\n",
       "      <td>22</td>\n",
       "      <td>2016-07-24</td>\n",
       "      <td>1.46</td>\n",
       "      <td>98321.14</td>\n",
       "      <td>11580.64</td>\n",
       "      <td>65195.63</td>\n",
       "      <td>13.73</td>\n",
       "      <td>21531.14</td>\n",
       "      <td>18639.29</td>\n",
       "      <td>241.85</td>\n",
       "      <td>2650.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2831</th>\n",
       "      <td>23</td>\n",
       "      <td>2016-07-17</td>\n",
       "      <td>1.31</td>\n",
       "      <td>89228.02</td>\n",
       "      <td>9273.69</td>\n",
       "      <td>64260.69</td>\n",
       "      <td>80.07</td>\n",
       "      <td>15613.57</td>\n",
       "      <td>13439.76</td>\n",
       "      <td>688.81</td>\n",
       "      <td>1485.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2832</th>\n",
       "      <td>24</td>\n",
       "      <td>2016-07-10</td>\n",
       "      <td>1.11</td>\n",
       "      <td>131630.13</td>\n",
       "      <td>20970.24</td>\n",
       "      <td>96581.82</td>\n",
       "      <td>46.49</td>\n",
       "      <td>14031.58</td>\n",
       "      <td>10876.00</td>\n",
       "      <td>470.58</td>\n",
       "      <td>2685.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2833</th>\n",
       "      <td>25</td>\n",
       "      <td>2016-07-03</td>\n",
       "      <td>1.42</td>\n",
       "      <td>115907.61</td>\n",
       "      <td>8373.77</td>\n",
       "      <td>82122.04</td>\n",
       "      <td>146.83</td>\n",
       "      <td>25264.97</td>\n",
       "      <td>21872.64</td>\n",
       "      <td>492.33</td>\n",
       "      <td>2900.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2834</th>\n",
       "      <td>26</td>\n",
       "      <td>2016-06-26</td>\n",
       "      <td>1.50</td>\n",
       "      <td>133086.66</td>\n",
       "      <td>7923.01</td>\n",
       "      <td>106656.84</td>\n",
       "      <td>37.42</td>\n",
       "      <td>18469.39</td>\n",
       "      <td>16479.75</td>\n",
       "      <td>419.64</td>\n",
       "      <td>1570.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2835</th>\n",
       "      <td>27</td>\n",
       "      <td>2016-06-19</td>\n",
       "      <td>1.42</td>\n",
       "      <td>112817.51</td>\n",
       "      <td>6766.63</td>\n",
       "      <td>85374.27</td>\n",
       "      <td>30.07</td>\n",
       "      <td>20646.54</td>\n",
       "      <td>18526.59</td>\n",
       "      <td>389.95</td>\n",
       "      <td>1730.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2836</th>\n",
       "      <td>28</td>\n",
       "      <td>2016-06-12</td>\n",
       "      <td>1.38</td>\n",
       "      <td>111394.50</td>\n",
       "      <td>7531.24</td>\n",
       "      <td>83771.34</td>\n",
       "      <td>81.25</td>\n",
       "      <td>20010.67</td>\n",
       "      <td>18368.49</td>\n",
       "      <td>282.18</td>\n",
       "      <td>1360.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2837</th>\n",
       "      <td>29</td>\n",
       "      <td>2016-06-05</td>\n",
       "      <td>1.47</td>\n",
       "      <td>115857.12</td>\n",
       "      <td>4288.46</td>\n",
       "      <td>92055.75</td>\n",
       "      <td>53.98</td>\n",
       "      <td>19458.93</td>\n",
       "      <td>17385.60</td>\n",
       "      <td>398.33</td>\n",
       "      <td>1675.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2016</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9096</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>0.97</td>\n",
       "      <td>43167806.09</td>\n",
       "      <td>15870677.70</td>\n",
       "      <td>11541844.87</td>\n",
       "      <td>652856.58</td>\n",
       "      <td>15102426.94</td>\n",
       "      <td>10844852.22</td>\n",
       "      <td>4023485.04</td>\n",
       "      <td>234089.68</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9097</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>0.87</td>\n",
       "      <td>62505646.52</td>\n",
       "      <td>21620180.90</td>\n",
       "      <td>20445501.03</td>\n",
       "      <td>1066830.22</td>\n",
       "      <td>19373134.37</td>\n",
       "      <td>13384586.80</td>\n",
       "      <td>5719096.61</td>\n",
       "      <td>269450.96</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9098</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.09</td>\n",
       "      <td>40171640.84</td>\n",
       "      <td>14551799.50</td>\n",
       "      <td>12119884.61</td>\n",
       "      <td>575974.74</td>\n",
       "      <td>12923981.99</td>\n",
       "      <td>9749412.19</td>\n",
       "      <td>3041125.42</td>\n",
       "      <td>133444.38</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9099</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.08</td>\n",
       "      <td>42939821.55</td>\n",
       "      <td>14218843.83</td>\n",
       "      <td>13929702.12</td>\n",
       "      <td>928815.12</td>\n",
       "      <td>13862460.48</td>\n",
       "      <td>9866218.28</td>\n",
       "      <td>3789722.90</td>\n",
       "      <td>206519.30</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9100</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.20</td>\n",
       "      <td>37299945.22</td>\n",
       "      <td>12600918.24</td>\n",
       "      <td>11866197.84</td>\n",
       "      <td>652808.40</td>\n",
       "      <td>12180020.74</td>\n",
       "      <td>8128241.88</td>\n",
       "      <td>3917569.95</td>\n",
       "      <td>134208.91</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9101</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.13</td>\n",
       "      <td>36703156.72</td>\n",
       "      <td>13730992.75</td>\n",
       "      <td>10781339.21</td>\n",
       "      <td>677714.86</td>\n",
       "      <td>11513109.90</td>\n",
       "      <td>8231766.23</td>\n",
       "      <td>3130919.10</td>\n",
       "      <td>150424.57</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9102</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>0.93</td>\n",
       "      <td>7667064.46</td>\n",
       "      <td>2567279.74</td>\n",
       "      <td>1912986.38</td>\n",
       "      <td>118289.91</td>\n",
       "      <td>3068508.43</td>\n",
       "      <td>1309580.19</td>\n",
       "      <td>1745630.06</td>\n",
       "      <td>13298.18</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9103</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>0.99</td>\n",
       "      <td>7254940.65</td>\n",
       "      <td>2099082.66</td>\n",
       "      <td>1707752.84</td>\n",
       "      <td>115997.93</td>\n",
       "      <td>3332107.22</td>\n",
       "      <td>1333247.05</td>\n",
       "      <td>1982086.02</td>\n",
       "      <td>16774.15</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9104</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.00</td>\n",
       "      <td>6906412.50</td>\n",
       "      <td>2442241.76</td>\n",
       "      <td>1695925.97</td>\n",
       "      <td>130983.00</td>\n",
       "      <td>2637261.77</td>\n",
       "      <td>1435608.59</td>\n",
       "      <td>1184730.56</td>\n",
       "      <td>16922.62</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9105</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>0.96</td>\n",
       "      <td>7371498.76</td>\n",
       "      <td>2676545.90</td>\n",
       "      <td>1748192.04</td>\n",
       "      <td>118365.31</td>\n",
       "      <td>2828395.51</td>\n",
       "      <td>1432984.96</td>\n",
       "      <td>1379886.53</td>\n",
       "      <td>15524.02</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9106</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>0.97</td>\n",
       "      <td>7408451.31</td>\n",
       "      <td>2154414.96</td>\n",
       "      <td>1740237.35</td>\n",
       "      <td>117766.27</td>\n",
       "      <td>3396032.73</td>\n",
       "      <td>1164132.42</td>\n",
       "      <td>2205336.14</td>\n",
       "      <td>26564.17</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9107</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>0.98</td>\n",
       "      <td>6783106.02</td>\n",
       "      <td>2511897.38</td>\n",
       "      <td>1645249.93</td>\n",
       "      <td>107420.55</td>\n",
       "      <td>2518538.16</td>\n",
       "      <td>1311830.11</td>\n",
       "      <td>1187897.07</td>\n",
       "      <td>18810.98</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9108</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>0.93</td>\n",
       "      <td>7463494.79</td>\n",
       "      <td>2646176.67</td>\n",
       "      <td>1633418.28</td>\n",
       "      <td>109146.92</td>\n",
       "      <td>3074752.92</td>\n",
       "      <td>1203367.03</td>\n",
       "      <td>1856207.85</td>\n",
       "      <td>15178.04</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9109</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>0.83</td>\n",
       "      <td>10565056.41</td>\n",
       "      <td>3121272.58</td>\n",
       "      <td>3294335.87</td>\n",
       "      <td>142553.21</td>\n",
       "      <td>4006894.75</td>\n",
       "      <td>1151399.33</td>\n",
       "      <td>2838239.39</td>\n",
       "      <td>17256.03</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9110</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.01</td>\n",
       "      <td>7007265.31</td>\n",
       "      <td>2718390.81</td>\n",
       "      <td>1664995.75</td>\n",
       "      <td>93165.88</td>\n",
       "      <td>2530712.87</td>\n",
       "      <td>1254504.07</td>\n",
       "      <td>1260049.46</td>\n",
       "      <td>16159.34</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9111</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.04</td>\n",
       "      <td>7053820.12</td>\n",
       "      <td>2218365.17</td>\n",
       "      <td>1811849.78</td>\n",
       "      <td>106001.28</td>\n",
       "      <td>2917603.89</td>\n",
       "      <td>1196963.03</td>\n",
       "      <td>1707643.76</td>\n",
       "      <td>12997.10</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9112</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.05</td>\n",
       "      <td>7577456.14</td>\n",
       "      <td>2249412.86</td>\n",
       "      <td>2028819.77</td>\n",
       "      <td>113257.03</td>\n",
       "      <td>3185966.48</td>\n",
       "      <td>1152416.21</td>\n",
       "      <td>2017353.32</td>\n",
       "      <td>16196.95</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9113</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.08</td>\n",
       "      <td>6358768.95</td>\n",
       "      <td>2061960.91</td>\n",
       "      <td>1706532.52</td>\n",
       "      <td>108441.55</td>\n",
       "      <td>2481833.97</td>\n",
       "      <td>1175889.89</td>\n",
       "      <td>1291212.75</td>\n",
       "      <td>14731.33</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9114</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>0.84</td>\n",
       "      <td>965185.06</td>\n",
       "      <td>438526.12</td>\n",
       "      <td>199585.90</td>\n",
       "      <td>11017.42</td>\n",
       "      <td>316055.62</td>\n",
       "      <td>153009.89</td>\n",
       "      <td>160999.10</td>\n",
       "      <td>2046.63</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9115</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>0.88</td>\n",
       "      <td>855251.17</td>\n",
       "      <td>457635.79</td>\n",
       "      <td>137597.04</td>\n",
       "      <td>8422.08</td>\n",
       "      <td>251596.26</td>\n",
       "      <td>151191.85</td>\n",
       "      <td>98535.60</td>\n",
       "      <td>1868.81</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9116</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>0.94</td>\n",
       "      <td>897607.12</td>\n",
       "      <td>467501.55</td>\n",
       "      <td>154130.63</td>\n",
       "      <td>11380.26</td>\n",
       "      <td>264594.68</td>\n",
       "      <td>152380.60</td>\n",
       "      <td>110322.16</td>\n",
       "      <td>1891.92</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9117</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>0.88</td>\n",
       "      <td>935934.10</td>\n",
       "      <td>454269.43</td>\n",
       "      <td>164856.57</td>\n",
       "      <td>9907.85</td>\n",
       "      <td>306900.25</td>\n",
       "      <td>164965.35</td>\n",
       "      <td>138399.68</td>\n",
       "      <td>3535.22</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9118</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>0.88</td>\n",
       "      <td>895671.55</td>\n",
       "      <td>431217.01</td>\n",
       "      <td>171532.79</td>\n",
       "      <td>10590.75</td>\n",
       "      <td>282331.00</td>\n",
       "      <td>125973.31</td>\n",
       "      <td>147040.26</td>\n",
       "      <td>9317.43</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9119</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>0.89</td>\n",
       "      <td>896808.98</td>\n",
       "      <td>421321.21</td>\n",
       "      <td>191798.82</td>\n",
       "      <td>10065.33</td>\n",
       "      <td>273623.62</td>\n",
       "      <td>130348.75</td>\n",
       "      <td>140202.81</td>\n",
       "      <td>3072.06</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9120</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1071952.06</td>\n",
       "      <td>544075.54</td>\n",
       "      <td>189862.10</td>\n",
       "      <td>7194.15</td>\n",
       "      <td>330820.27</td>\n",
       "      <td>113338.76</td>\n",
       "      <td>215753.74</td>\n",
       "      <td>1727.77</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9121</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>0.76</td>\n",
       "      <td>1272039.80</td>\n",
       "      <td>531469.08</td>\n",
       "      <td>368948.26</td>\n",
       "      <td>13078.20</td>\n",
       "      <td>358544.26</td>\n",
       "      <td>127833.03</td>\n",
       "      <td>229786.03</td>\n",
       "      <td>925.20</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9122</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>0.85</td>\n",
       "      <td>957086.16</td>\n",
       "      <td>479147.93</td>\n",
       "      <td>179489.19</td>\n",
       "      <td>7314.98</td>\n",
       "      <td>291134.06</td>\n",
       "      <td>143430.96</td>\n",
       "      <td>147376.43</td>\n",
       "      <td>326.67</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9123</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>0.84</td>\n",
       "      <td>1020913.20</td>\n",
       "      <td>505263.29</td>\n",
       "      <td>177911.40</td>\n",
       "      <td>9468.95</td>\n",
       "      <td>328269.56</td>\n",
       "      <td>118978.50</td>\n",
       "      <td>209131.06</td>\n",
       "      <td>160.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9124</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>0.90</td>\n",
       "      <td>950954.60</td>\n",
       "      <td>463945.73</td>\n",
       "      <td>188126.02</td>\n",
       "      <td>11227.47</td>\n",
       "      <td>287655.38</td>\n",
       "      <td>125408.69</td>\n",
       "      <td>162040.02</td>\n",
       "      <td>206.67</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9125</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>0.88</td>\n",
       "      <td>880266.52</td>\n",
       "      <td>436282.38</td>\n",
       "      <td>178669.53</td>\n",
       "      <td>9467.11</td>\n",
       "      <td>255847.50</td>\n",
       "      <td>99686.92</td>\n",
       "      <td>155870.58</td>\n",
       "      <td>290.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6318 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0        Date  AveragePrice  Total Volume         4046  \\\n",
       "2808           0  2016-12-25          1.52      73341.73      3202.39   \n",
       "2809           1  2016-12-18          1.53      68938.53      3345.36   \n",
       "2810           2  2016-12-11          1.49      71777.85      2323.39   \n",
       "2811           3  2016-12-04          1.48     113031.96      6530.78   \n",
       "2812           4  2016-11-27          1.52      58171.89      2793.99   \n",
       "2813           5  2016-11-20          1.56      70089.51      3675.63   \n",
       "2814           6  2016-11-13          1.62      63608.01      3523.63   \n",
       "2815           7  2016-11-06          1.63      57178.20      3212.04   \n",
       "2816           8  2016-10-30          1.46      58375.10      3187.14   \n",
       "2817           9  2016-10-23          1.19      92080.35      4222.93   \n",
       "2818          10  2016-10-16          1.40      69060.90      4027.42   \n",
       "2819          11  2016-10-09          1.13     101087.84      3641.46   \n",
       "2820          12  2016-10-02          1.51      75480.26      4109.22   \n",
       "2821          13  2016-09-25          1.62      96853.15      7658.55   \n",
       "2822          14  2016-09-18          1.39      79513.63      6624.37   \n",
       "2823          15  2016-09-11          1.37      81473.15      6258.88   \n",
       "2824          16  2016-09-04          1.44      95456.26     14741.13   \n",
       "2825          17  2016-08-28          1.18     145323.22     34912.97   \n",
       "2826          18  2016-08-21          1.43      94882.79     14520.36   \n",
       "2827          19  2016-08-14          1.20     110528.09     24000.62   \n",
       "2828          20  2016-08-07          1.48      99683.11     14670.87   \n",
       "2829          21  2016-07-31          1.61     125586.57      9293.65   \n",
       "2830          22  2016-07-24          1.46      98321.14     11580.64   \n",
       "2831          23  2016-07-17          1.31      89228.02      9273.69   \n",
       "2832          24  2016-07-10          1.11     131630.13     20970.24   \n",
       "2833          25  2016-07-03          1.42     115907.61      8373.77   \n",
       "2834          26  2016-06-26          1.50     133086.66      7923.01   \n",
       "2835          27  2016-06-19          1.42     112817.51      6766.63   \n",
       "2836          28  2016-06-12          1.38     111394.50      7531.24   \n",
       "2837          29  2016-06-05          1.47     115857.12      4288.46   \n",
       "...          ...         ...           ...           ...          ...   \n",
       "9096           6  2018-02-11          0.97   43167806.09  15870677.70   \n",
       "9097           7  2018-02-04          0.87   62505646.52  21620180.90   \n",
       "9098           8  2018-01-28          1.09   40171640.84  14551799.50   \n",
       "9099           9  2018-01-21          1.08   42939821.55  14218843.83   \n",
       "9100          10  2018-01-14          1.20   37299945.22  12600918.24   \n",
       "9101          11  2018-01-07          1.13   36703156.72  13730992.75   \n",
       "9102           0  2018-03-25          0.93    7667064.46   2567279.74   \n",
       "9103           1  2018-03-18          0.99    7254940.65   2099082.66   \n",
       "9104           2  2018-03-11          1.00    6906412.50   2442241.76   \n",
       "9105           3  2018-03-04          0.96    7371498.76   2676545.90   \n",
       "9106           4  2018-02-25          0.97    7408451.31   2154414.96   \n",
       "9107           5  2018-02-18          0.98    6783106.02   2511897.38   \n",
       "9108           6  2018-02-11          0.93    7463494.79   2646176.67   \n",
       "9109           7  2018-02-04          0.83   10565056.41   3121272.58   \n",
       "9110           8  2018-01-28          1.01    7007265.31   2718390.81   \n",
       "9111           9  2018-01-21          1.04    7053820.12   2218365.17   \n",
       "9112          10  2018-01-14          1.05    7577456.14   2249412.86   \n",
       "9113          11  2018-01-07          1.08    6358768.95   2061960.91   \n",
       "9114           0  2018-03-25          0.84     965185.06    438526.12   \n",
       "9115           1  2018-03-18          0.88     855251.17    457635.79   \n",
       "9116           2  2018-03-11          0.94     897607.12    467501.55   \n",
       "9117           3  2018-03-04          0.88     935934.10    454269.43   \n",
       "9118           4  2018-02-25          0.88     895671.55    431217.01   \n",
       "9119           5  2018-02-18          0.89     896808.98    421321.21   \n",
       "9120           6  2018-02-11          0.75    1071952.06    544075.54   \n",
       "9121           7  2018-02-04          0.76    1272039.80    531469.08   \n",
       "9122           8  2018-01-28          0.85     957086.16    479147.93   \n",
       "9123           9  2018-01-21          0.84    1020913.20    505263.29   \n",
       "9124          10  2018-01-14          0.90     950954.60    463945.73   \n",
       "9125          11  2018-01-07          0.88     880266.52    436282.38   \n",
       "\n",
       "             4225        4770   Total Bags   Small Bags  Large Bags  \\\n",
       "2808     58280.33      426.92     11432.09     11017.32      411.83   \n",
       "2809     55949.79      138.72      9504.66      8876.65      587.73   \n",
       "2810     56545.79       86.65     12822.02     12176.75      645.27   \n",
       "2811     99746.05       50.84      6704.29      6476.12      228.17   \n",
       "2812     47106.18       18.14      8253.58      7973.98      279.60   \n",
       "2813     56898.54       11.00      9504.34      9238.40      209.00   \n",
       "2814     49837.68       34.00     10212.70      9790.67      422.03   \n",
       "2815     43024.32       36.40     10905.44     10474.09      431.35   \n",
       "2816     45898.52       54.31      9235.13      9153.12       82.01   \n",
       "2817     77537.36       46.00     10274.06     10160.26      113.80   \n",
       "2818     54186.55       53.77     10793.16     10434.39      358.77   \n",
       "2819     87174.41      102.15     10169.82      9744.41      425.41   \n",
       "2820     57515.76       84.08     13771.20     13345.52      425.68   \n",
       "2821     79425.81       43.25      9725.54      9586.80      138.74   \n",
       "2822     63384.56       37.48      9467.22      8958.14      509.08   \n",
       "2823     63511.85       42.26     11660.16     10839.17      815.99   \n",
       "2824     64966.75       88.11     15660.27     15340.19      220.08   \n",
       "2825     94928.79       53.85     15427.61     14367.64      269.97   \n",
       "2826     63416.88       28.03     16917.52     15811.00      286.52   \n",
       "2827     72970.23       26.76     13530.48     12434.82      350.10   \n",
       "2828     69054.28       10.90     15947.06     14597.20      178.19   \n",
       "2829     96915.41       25.46     19352.05     18803.23       78.82   \n",
       "2830     65195.63       13.73     21531.14     18639.29      241.85   \n",
       "2831     64260.69       80.07     15613.57     13439.76      688.81   \n",
       "2832     96581.82       46.49     14031.58     10876.00      470.58   \n",
       "2833     82122.04      146.83     25264.97     21872.64      492.33   \n",
       "2834    106656.84       37.42     18469.39     16479.75      419.64   \n",
       "2835     85374.27       30.07     20646.54     18526.59      389.95   \n",
       "2836     83771.34       81.25     20010.67     18368.49      282.18   \n",
       "2837     92055.75       53.98     19458.93     17385.60      398.33   \n",
       "...           ...         ...          ...          ...         ...   \n",
       "9096  11541844.87   652856.58  15102426.94  10844852.22  4023485.04   \n",
       "9097  20445501.03  1066830.22  19373134.37  13384586.80  5719096.61   \n",
       "9098  12119884.61   575974.74  12923981.99   9749412.19  3041125.42   \n",
       "9099  13929702.12   928815.12  13862460.48   9866218.28  3789722.90   \n",
       "9100  11866197.84   652808.40  12180020.74   8128241.88  3917569.95   \n",
       "9101  10781339.21   677714.86  11513109.90   8231766.23  3130919.10   \n",
       "9102   1912986.38   118289.91   3068508.43   1309580.19  1745630.06   \n",
       "9103   1707752.84   115997.93   3332107.22   1333247.05  1982086.02   \n",
       "9104   1695925.97   130983.00   2637261.77   1435608.59  1184730.56   \n",
       "9105   1748192.04   118365.31   2828395.51   1432984.96  1379886.53   \n",
       "9106   1740237.35   117766.27   3396032.73   1164132.42  2205336.14   \n",
       "9107   1645249.93   107420.55   2518538.16   1311830.11  1187897.07   \n",
       "9108   1633418.28   109146.92   3074752.92   1203367.03  1856207.85   \n",
       "9109   3294335.87   142553.21   4006894.75   1151399.33  2838239.39   \n",
       "9110   1664995.75    93165.88   2530712.87   1254504.07  1260049.46   \n",
       "9111   1811849.78   106001.28   2917603.89   1196963.03  1707643.76   \n",
       "9112   2028819.77   113257.03   3185966.48   1152416.21  2017353.32   \n",
       "9113   1706532.52   108441.55   2481833.97   1175889.89  1291212.75   \n",
       "9114    199585.90    11017.42    316055.62    153009.89   160999.10   \n",
       "9115    137597.04     8422.08    251596.26    151191.85    98535.60   \n",
       "9116    154130.63    11380.26    264594.68    152380.60   110322.16   \n",
       "9117    164856.57     9907.85    306900.25    164965.35   138399.68   \n",
       "9118    171532.79    10590.75    282331.00    125973.31   147040.26   \n",
       "9119    191798.82    10065.33    273623.62    130348.75   140202.81   \n",
       "9120    189862.10     7194.15    330820.27    113338.76   215753.74   \n",
       "9121    368948.26    13078.20    358544.26    127833.03   229786.03   \n",
       "9122    179489.19     7314.98    291134.06    143430.96   147376.43   \n",
       "9123    177911.40     9468.95    328269.56    118978.50   209131.06   \n",
       "9124    188126.02    11227.47    287655.38    125408.69   162040.02   \n",
       "9125    178669.53     9467.11    255847.50     99686.92   155870.58   \n",
       "\n",
       "      XLarge Bags          type  year            region  \n",
       "2808         2.94  conventional  2016            Albany  \n",
       "2809        40.28  conventional  2016            Albany  \n",
       "2810         0.00  conventional  2016            Albany  \n",
       "2811         0.00  conventional  2016            Albany  \n",
       "2812         0.00  conventional  2016            Albany  \n",
       "2813        56.94  conventional  2016            Albany  \n",
       "2814         0.00  conventional  2016            Albany  \n",
       "2815         0.00  conventional  2016            Albany  \n",
       "2816         0.00  conventional  2016            Albany  \n",
       "2817         0.00  conventional  2016            Albany  \n",
       "2818         0.00  conventional  2016            Albany  \n",
       "2819         0.00  conventional  2016            Albany  \n",
       "2820         0.00  conventional  2016            Albany  \n",
       "2821         0.00  conventional  2016            Albany  \n",
       "2822         0.00  conventional  2016            Albany  \n",
       "2823         5.00  conventional  2016            Albany  \n",
       "2824       100.00  conventional  2016            Albany  \n",
       "2825       790.00  conventional  2016            Albany  \n",
       "2826       820.00  conventional  2016            Albany  \n",
       "2827       745.56  conventional  2016            Albany  \n",
       "2828      1171.67  conventional  2016            Albany  \n",
       "2829       470.00  conventional  2016            Albany  \n",
       "2830      2650.00  conventional  2016            Albany  \n",
       "2831      1485.00  conventional  2016            Albany  \n",
       "2832      2685.00  conventional  2016            Albany  \n",
       "2833      2900.00  conventional  2016            Albany  \n",
       "2834      1570.00  conventional  2016            Albany  \n",
       "2835      1730.00  conventional  2016            Albany  \n",
       "2836      1360.00  conventional  2016            Albany  \n",
       "2837      1675.00  conventional  2016            Albany  \n",
       "...           ...           ...   ...               ...  \n",
       "9096    234089.68  conventional  2018           TotalUS  \n",
       "9097    269450.96  conventional  2018           TotalUS  \n",
       "9098    133444.38  conventional  2018           TotalUS  \n",
       "9099    206519.30  conventional  2018           TotalUS  \n",
       "9100    134208.91  conventional  2018           TotalUS  \n",
       "9101    150424.57  conventional  2018           TotalUS  \n",
       "9102     13298.18  conventional  2018              West  \n",
       "9103     16774.15  conventional  2018              West  \n",
       "9104     16922.62  conventional  2018              West  \n",
       "9105     15524.02  conventional  2018              West  \n",
       "9106     26564.17  conventional  2018              West  \n",
       "9107     18810.98  conventional  2018              West  \n",
       "9108     15178.04  conventional  2018              West  \n",
       "9109     17256.03  conventional  2018              West  \n",
       "9110     16159.34  conventional  2018              West  \n",
       "9111     12997.10  conventional  2018              West  \n",
       "9112     16196.95  conventional  2018              West  \n",
       "9113     14731.33  conventional  2018              West  \n",
       "9114      2046.63  conventional  2018  WestTexNewMexico  \n",
       "9115      1868.81  conventional  2018  WestTexNewMexico  \n",
       "9116      1891.92  conventional  2018  WestTexNewMexico  \n",
       "9117      3535.22  conventional  2018  WestTexNewMexico  \n",
       "9118      9317.43  conventional  2018  WestTexNewMexico  \n",
       "9119      3072.06  conventional  2018  WestTexNewMexico  \n",
       "9120      1727.77  conventional  2018  WestTexNewMexico  \n",
       "9121       925.20  conventional  2018  WestTexNewMexico  \n",
       "9122       326.67  conventional  2018  WestTexNewMexico  \n",
       "9123       160.00  conventional  2018  WestTexNewMexico  \n",
       "9124       206.67  conventional  2018  WestTexNewMexico  \n",
       "9125       290.00  conventional  2018  WestTexNewMexico  \n",
       "\n",
       "[6318 rows x 14 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_2015_oragnic = avocado.loc[(avocado[\"year\"] != 2015) & (avocado[\"type\"] != \"organic\")]\n",
    "no_2015_oragnic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how we had to use paranthesis to split up our conditional statements while filtering."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding new columns\n",
    "\n",
    "To add in a new column named *new_column* in pandas, we can use **df[\"new_column\"]** and assign it to be whatever values we want for the column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "      <th>True</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>1.33</td>\n",
       "      <td>64236.62</td>\n",
       "      <td>1036.74</td>\n",
       "      <td>54454.85</td>\n",
       "      <td>48.16</td>\n",
       "      <td>8696.87</td>\n",
       "      <td>8603.62</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-12-20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>54876.98</td>\n",
       "      <td>674.28</td>\n",
       "      <td>44638.81</td>\n",
       "      <td>58.33</td>\n",
       "      <td>9505.56</td>\n",
       "      <td>9408.07</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-12-13</td>\n",
       "      <td>0.93</td>\n",
       "      <td>118220.22</td>\n",
       "      <td>794.70</td>\n",
       "      <td>109149.67</td>\n",
       "      <td>130.50</td>\n",
       "      <td>8145.35</td>\n",
       "      <td>8042.21</td>\n",
       "      <td>103.14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-12-06</td>\n",
       "      <td>1.08</td>\n",
       "      <td>78992.15</td>\n",
       "      <td>1132.00</td>\n",
       "      <td>71976.41</td>\n",
       "      <td>72.58</td>\n",
       "      <td>5811.16</td>\n",
       "      <td>5677.40</td>\n",
       "      <td>133.76</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-11-29</td>\n",
       "      <td>1.28</td>\n",
       "      <td>51039.60</td>\n",
       "      <td>941.48</td>\n",
       "      <td>43838.39</td>\n",
       "      <td>75.78</td>\n",
       "      <td>6183.95</td>\n",
       "      <td>5986.26</td>\n",
       "      <td>197.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>2015-11-22</td>\n",
       "      <td>1.26</td>\n",
       "      <td>55979.78</td>\n",
       "      <td>1184.27</td>\n",
       "      <td>48067.99</td>\n",
       "      <td>43.61</td>\n",
       "      <td>6683.91</td>\n",
       "      <td>6556.47</td>\n",
       "      <td>127.44</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>2015-11-15</td>\n",
       "      <td>0.99</td>\n",
       "      <td>83453.76</td>\n",
       "      <td>1368.92</td>\n",
       "      <td>73672.72</td>\n",
       "      <td>93.26</td>\n",
       "      <td>8318.86</td>\n",
       "      <td>8196.81</td>\n",
       "      <td>122.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>2015-11-08</td>\n",
       "      <td>0.98</td>\n",
       "      <td>109428.33</td>\n",
       "      <td>703.75</td>\n",
       "      <td>101815.36</td>\n",
       "      <td>80.00</td>\n",
       "      <td>6829.22</td>\n",
       "      <td>6266.85</td>\n",
       "      <td>562.37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2015-11-01</td>\n",
       "      <td>1.02</td>\n",
       "      <td>99811.42</td>\n",
       "      <td>1022.15</td>\n",
       "      <td>87315.57</td>\n",
       "      <td>85.34</td>\n",
       "      <td>11388.36</td>\n",
       "      <td>11104.53</td>\n",
       "      <td>283.83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>2015-10-25</td>\n",
       "      <td>1.07</td>\n",
       "      <td>74338.76</td>\n",
       "      <td>842.40</td>\n",
       "      <td>64757.44</td>\n",
       "      <td>113.00</td>\n",
       "      <td>8625.92</td>\n",
       "      <td>8061.47</td>\n",
       "      <td>564.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>2015-10-18</td>\n",
       "      <td>1.12</td>\n",
       "      <td>84843.44</td>\n",
       "      <td>924.86</td>\n",
       "      <td>75595.85</td>\n",
       "      <td>117.07</td>\n",
       "      <td>8205.66</td>\n",
       "      <td>7877.86</td>\n",
       "      <td>327.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>2015-10-11</td>\n",
       "      <td>1.28</td>\n",
       "      <td>64489.17</td>\n",
       "      <td>1582.03</td>\n",
       "      <td>52677.92</td>\n",
       "      <td>105.32</td>\n",
       "      <td>10123.90</td>\n",
       "      <td>9866.27</td>\n",
       "      <td>257.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>1.31</td>\n",
       "      <td>61007.10</td>\n",
       "      <td>2268.32</td>\n",
       "      <td>49880.67</td>\n",
       "      <td>101.36</td>\n",
       "      <td>8756.75</td>\n",
       "      <td>8379.98</td>\n",
       "      <td>376.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>2015-09-27</td>\n",
       "      <td>0.99</td>\n",
       "      <td>106803.39</td>\n",
       "      <td>1204.88</td>\n",
       "      <td>99409.21</td>\n",
       "      <td>154.84</td>\n",
       "      <td>6034.46</td>\n",
       "      <td>5888.87</td>\n",
       "      <td>145.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>2015-09-20</td>\n",
       "      <td>1.33</td>\n",
       "      <td>69759.01</td>\n",
       "      <td>1028.03</td>\n",
       "      <td>59313.12</td>\n",
       "      <td>150.50</td>\n",
       "      <td>9267.36</td>\n",
       "      <td>8489.10</td>\n",
       "      <td>778.26</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>2015-09-13</td>\n",
       "      <td>1.28</td>\n",
       "      <td>76111.27</td>\n",
       "      <td>985.73</td>\n",
       "      <td>65696.86</td>\n",
       "      <td>142.00</td>\n",
       "      <td>9286.68</td>\n",
       "      <td>8665.19</td>\n",
       "      <td>621.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>2015-09-06</td>\n",
       "      <td>1.11</td>\n",
       "      <td>99172.96</td>\n",
       "      <td>879.45</td>\n",
       "      <td>90062.62</td>\n",
       "      <td>240.79</td>\n",
       "      <td>7990.10</td>\n",
       "      <td>7762.87</td>\n",
       "      <td>227.23</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>2015-08-30</td>\n",
       "      <td>1.07</td>\n",
       "      <td>105693.84</td>\n",
       "      <td>689.01</td>\n",
       "      <td>94362.67</td>\n",
       "      <td>335.43</td>\n",
       "      <td>10306.73</td>\n",
       "      <td>10218.93</td>\n",
       "      <td>87.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>2015-08-23</td>\n",
       "      <td>1.34</td>\n",
       "      <td>79992.09</td>\n",
       "      <td>733.16</td>\n",
       "      <td>67933.79</td>\n",
       "      <td>444.78</td>\n",
       "      <td>10880.36</td>\n",
       "      <td>10745.79</td>\n",
       "      <td>134.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>2015-08-16</td>\n",
       "      <td>1.33</td>\n",
       "      <td>80043.78</td>\n",
       "      <td>539.65</td>\n",
       "      <td>68666.01</td>\n",
       "      <td>394.90</td>\n",
       "      <td>10443.22</td>\n",
       "      <td>10297.68</td>\n",
       "      <td>145.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>2015-08-09</td>\n",
       "      <td>1.12</td>\n",
       "      <td>111140.93</td>\n",
       "      <td>584.63</td>\n",
       "      <td>100961.46</td>\n",
       "      <td>368.95</td>\n",
       "      <td>9225.89</td>\n",
       "      <td>9116.34</td>\n",
       "      <td>109.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>2015-08-02</td>\n",
       "      <td>1.45</td>\n",
       "      <td>75133.10</td>\n",
       "      <td>509.94</td>\n",
       "      <td>62035.06</td>\n",
       "      <td>741.08</td>\n",
       "      <td>11847.02</td>\n",
       "      <td>11768.52</td>\n",
       "      <td>78.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>2015-07-26</td>\n",
       "      <td>1.11</td>\n",
       "      <td>106757.10</td>\n",
       "      <td>648.75</td>\n",
       "      <td>91949.05</td>\n",
       "      <td>966.61</td>\n",
       "      <td>13192.69</td>\n",
       "      <td>13061.53</td>\n",
       "      <td>131.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>2015-07-19</td>\n",
       "      <td>1.26</td>\n",
       "      <td>96617.00</td>\n",
       "      <td>1042.10</td>\n",
       "      <td>82049.40</td>\n",
       "      <td>2238.02</td>\n",
       "      <td>11287.48</td>\n",
       "      <td>11103.49</td>\n",
       "      <td>183.99</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>2015-07-12</td>\n",
       "      <td>1.05</td>\n",
       "      <td>124055.31</td>\n",
       "      <td>672.25</td>\n",
       "      <td>94693.52</td>\n",
       "      <td>4257.64</td>\n",
       "      <td>24431.90</td>\n",
       "      <td>24290.08</td>\n",
       "      <td>108.49</td>\n",
       "      <td>33.33</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>2015-07-05</td>\n",
       "      <td>1.35</td>\n",
       "      <td>109252.12</td>\n",
       "      <td>869.45</td>\n",
       "      <td>72600.55</td>\n",
       "      <td>5883.16</td>\n",
       "      <td>29898.96</td>\n",
       "      <td>29663.19</td>\n",
       "      <td>235.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>2015-06-28</td>\n",
       "      <td>1.37</td>\n",
       "      <td>89534.81</td>\n",
       "      <td>664.23</td>\n",
       "      <td>57545.79</td>\n",
       "      <td>4662.71</td>\n",
       "      <td>26662.08</td>\n",
       "      <td>26311.76</td>\n",
       "      <td>350.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>2015-06-21</td>\n",
       "      <td>1.27</td>\n",
       "      <td>104849.39</td>\n",
       "      <td>804.01</td>\n",
       "      <td>76688.55</td>\n",
       "      <td>5481.18</td>\n",
       "      <td>21875.65</td>\n",
       "      <td>21662.00</td>\n",
       "      <td>213.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>2015-06-14</td>\n",
       "      <td>1.32</td>\n",
       "      <td>89631.30</td>\n",
       "      <td>850.58</td>\n",
       "      <td>55400.94</td>\n",
       "      <td>4377.19</td>\n",
       "      <td>29002.59</td>\n",
       "      <td>28343.14</td>\n",
       "      <td>659.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>2015-06-07</td>\n",
       "      <td>1.07</td>\n",
       "      <td>122743.06</td>\n",
       "      <td>656.71</td>\n",
       "      <td>99220.82</td>\n",
       "      <td>90.32</td>\n",
       "      <td>22775.21</td>\n",
       "      <td>22314.99</td>\n",
       "      <td>460.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18219</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1317000.47</td>\n",
       "      <td>98465.26</td>\n",
       "      <td>270798.27</td>\n",
       "      <td>1839.80</td>\n",
       "      <td>945638.02</td>\n",
       "      <td>768242.42</td>\n",
       "      <td>177144.00</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18220</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1384683.41</td>\n",
       "      <td>117922.52</td>\n",
       "      <td>287724.61</td>\n",
       "      <td>1703.52</td>\n",
       "      <td>977084.84</td>\n",
       "      <td>774695.74</td>\n",
       "      <td>201878.69</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18221</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.61</td>\n",
       "      <td>1336979.09</td>\n",
       "      <td>118616.17</td>\n",
       "      <td>280080.34</td>\n",
       "      <td>1270.61</td>\n",
       "      <td>936859.49</td>\n",
       "      <td>796104.27</td>\n",
       "      <td>140652.84</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18222</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1283987.65</td>\n",
       "      <td>108705.28</td>\n",
       "      <td>259172.13</td>\n",
       "      <td>1490.02</td>\n",
       "      <td>914409.26</td>\n",
       "      <td>710654.40</td>\n",
       "      <td>203526.59</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18223</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.59</td>\n",
       "      <td>1476651.08</td>\n",
       "      <td>145680.62</td>\n",
       "      <td>323669.83</td>\n",
       "      <td>1580.01</td>\n",
       "      <td>1005593.78</td>\n",
       "      <td>858772.69</td>\n",
       "      <td>146808.97</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18224</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1517332.70</td>\n",
       "      <td>129541.43</td>\n",
       "      <td>296490.29</td>\n",
       "      <td>1289.07</td>\n",
       "      <td>1089861.24</td>\n",
       "      <td>915452.78</td>\n",
       "      <td>174381.57</td>\n",
       "      <td>26.89</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18225</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.60</td>\n",
       "      <td>271723.08</td>\n",
       "      <td>26996.28</td>\n",
       "      <td>77861.39</td>\n",
       "      <td>117.56</td>\n",
       "      <td>166747.85</td>\n",
       "      <td>87108.00</td>\n",
       "      <td>79495.39</td>\n",
       "      <td>144.46</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18226</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.73</td>\n",
       "      <td>210067.47</td>\n",
       "      <td>33437.98</td>\n",
       "      <td>47165.54</td>\n",
       "      <td>110.40</td>\n",
       "      <td>129353.55</td>\n",
       "      <td>73163.12</td>\n",
       "      <td>56020.24</td>\n",
       "      <td>170.19</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18227</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.63</td>\n",
       "      <td>264691.87</td>\n",
       "      <td>27566.25</td>\n",
       "      <td>60383.57</td>\n",
       "      <td>276.42</td>\n",
       "      <td>176465.63</td>\n",
       "      <td>107174.93</td>\n",
       "      <td>69290.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18228</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.46</td>\n",
       "      <td>347373.17</td>\n",
       "      <td>25990.60</td>\n",
       "      <td>71213.19</td>\n",
       "      <td>79.01</td>\n",
       "      <td>250090.37</td>\n",
       "      <td>85835.17</td>\n",
       "      <td>164087.33</td>\n",
       "      <td>167.87</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18229</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.49</td>\n",
       "      <td>301985.61</td>\n",
       "      <td>34200.18</td>\n",
       "      <td>49139.34</td>\n",
       "      <td>85.58</td>\n",
       "      <td>218560.51</td>\n",
       "      <td>99989.62</td>\n",
       "      <td>118314.77</td>\n",
       "      <td>256.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18230</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.64</td>\n",
       "      <td>224798.60</td>\n",
       "      <td>30149.00</td>\n",
       "      <td>38800.64</td>\n",
       "      <td>123.13</td>\n",
       "      <td>155725.83</td>\n",
       "      <td>120428.13</td>\n",
       "      <td>35257.73</td>\n",
       "      <td>39.97</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18231</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.47</td>\n",
       "      <td>275248.53</td>\n",
       "      <td>24732.55</td>\n",
       "      <td>61713.53</td>\n",
       "      <td>243.00</td>\n",
       "      <td>188559.45</td>\n",
       "      <td>88497.05</td>\n",
       "      <td>99810.80</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18232</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.41</td>\n",
       "      <td>283378.47</td>\n",
       "      <td>22474.66</td>\n",
       "      <td>55360.49</td>\n",
       "      <td>133.41</td>\n",
       "      <td>205409.91</td>\n",
       "      <td>70232.59</td>\n",
       "      <td>134666.91</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18233</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.80</td>\n",
       "      <td>185974.53</td>\n",
       "      <td>22918.40</td>\n",
       "      <td>33051.14</td>\n",
       "      <td>93.52</td>\n",
       "      <td>129911.47</td>\n",
       "      <td>77822.23</td>\n",
       "      <td>51986.86</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18234</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.83</td>\n",
       "      <td>189317.99</td>\n",
       "      <td>27049.44</td>\n",
       "      <td>33561.32</td>\n",
       "      <td>439.47</td>\n",
       "      <td>128267.76</td>\n",
       "      <td>76091.99</td>\n",
       "      <td>51947.50</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18235</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.82</td>\n",
       "      <td>207999.67</td>\n",
       "      <td>33869.12</td>\n",
       "      <td>47435.14</td>\n",
       "      <td>433.52</td>\n",
       "      <td>126261.89</td>\n",
       "      <td>89115.78</td>\n",
       "      <td>37133.99</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18236</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>297190.60</td>\n",
       "      <td>34734.97</td>\n",
       "      <td>62967.74</td>\n",
       "      <td>157.77</td>\n",
       "      <td>199330.12</td>\n",
       "      <td>103761.55</td>\n",
       "      <td>95544.39</td>\n",
       "      <td>24.18</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18237</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>15303.40</td>\n",
       "      <td>2325.30</td>\n",
       "      <td>2171.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10806.44</td>\n",
       "      <td>10569.80</td>\n",
       "      <td>236.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18238</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>15896.38</td>\n",
       "      <td>2055.35</td>\n",
       "      <td>1499.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12341.48</td>\n",
       "      <td>12114.81</td>\n",
       "      <td>226.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18239</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>22128.42</td>\n",
       "      <td>2162.67</td>\n",
       "      <td>3194.25</td>\n",
       "      <td>8.93</td>\n",
       "      <td>16762.57</td>\n",
       "      <td>16510.32</td>\n",
       "      <td>252.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18240</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.54</td>\n",
       "      <td>17393.30</td>\n",
       "      <td>1832.24</td>\n",
       "      <td>1905.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13655.49</td>\n",
       "      <td>13401.93</td>\n",
       "      <td>253.56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18241</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.57</td>\n",
       "      <td>18421.24</td>\n",
       "      <td>1974.26</td>\n",
       "      <td>2482.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13964.33</td>\n",
       "      <td>13698.27</td>\n",
       "      <td>266.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18242</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>17597.12</td>\n",
       "      <td>1892.05</td>\n",
       "      <td>1928.36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13776.71</td>\n",
       "      <td>13553.53</td>\n",
       "      <td>223.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18243</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.57</td>\n",
       "      <td>15986.17</td>\n",
       "      <td>1924.28</td>\n",
       "      <td>1368.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12693.57</td>\n",
       "      <td>12437.35</td>\n",
       "      <td>256.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18244</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.63</td>\n",
       "      <td>17074.83</td>\n",
       "      <td>2046.96</td>\n",
       "      <td>1529.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13498.67</td>\n",
       "      <td>13066.82</td>\n",
       "      <td>431.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18245</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.71</td>\n",
       "      <td>13888.04</td>\n",
       "      <td>1191.70</td>\n",
       "      <td>3431.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9264.84</td>\n",
       "      <td>8940.04</td>\n",
       "      <td>324.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.87</td>\n",
       "      <td>13766.76</td>\n",
       "      <td>1191.92</td>\n",
       "      <td>2452.79</td>\n",
       "      <td>727.94</td>\n",
       "      <td>9394.11</td>\n",
       "      <td>9351.80</td>\n",
       "      <td>42.31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18247</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.93</td>\n",
       "      <td>16205.22</td>\n",
       "      <td>1527.63</td>\n",
       "      <td>2981.04</td>\n",
       "      <td>727.01</td>\n",
       "      <td>10969.54</td>\n",
       "      <td>10919.54</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18248</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.62</td>\n",
       "      <td>17489.58</td>\n",
       "      <td>2894.77</td>\n",
       "      <td>2356.13</td>\n",
       "      <td>224.53</td>\n",
       "      <td>12014.15</td>\n",
       "      <td>11988.14</td>\n",
       "      <td>26.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18249 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0        Date  AveragePrice  Total Volume       4046  \\\n",
       "0               0  2015-12-27          1.33      64236.62    1036.74   \n",
       "1               1  2015-12-20          1.35      54876.98     674.28   \n",
       "2               2  2015-12-13          0.93     118220.22     794.70   \n",
       "3               3  2015-12-06          1.08      78992.15    1132.00   \n",
       "4               4  2015-11-29          1.28      51039.60     941.48   \n",
       "5               5  2015-11-22          1.26      55979.78    1184.27   \n",
       "6               6  2015-11-15          0.99      83453.76    1368.92   \n",
       "7               7  2015-11-08          0.98     109428.33     703.75   \n",
       "8               8  2015-11-01          1.02      99811.42    1022.15   \n",
       "9               9  2015-10-25          1.07      74338.76     842.40   \n",
       "10             10  2015-10-18          1.12      84843.44     924.86   \n",
       "11             11  2015-10-11          1.28      64489.17    1582.03   \n",
       "12             12  2015-10-04          1.31      61007.10    2268.32   \n",
       "13             13  2015-09-27          0.99     106803.39    1204.88   \n",
       "14             14  2015-09-20          1.33      69759.01    1028.03   \n",
       "15             15  2015-09-13          1.28      76111.27     985.73   \n",
       "16             16  2015-09-06          1.11      99172.96     879.45   \n",
       "17             17  2015-08-30          1.07     105693.84     689.01   \n",
       "18             18  2015-08-23          1.34      79992.09     733.16   \n",
       "19             19  2015-08-16          1.33      80043.78     539.65   \n",
       "20             20  2015-08-09          1.12     111140.93     584.63   \n",
       "21             21  2015-08-02          1.45      75133.10     509.94   \n",
       "22             22  2015-07-26          1.11     106757.10     648.75   \n",
       "23             23  2015-07-19          1.26      96617.00    1042.10   \n",
       "24             24  2015-07-12          1.05     124055.31     672.25   \n",
       "25             25  2015-07-05          1.35     109252.12     869.45   \n",
       "26             26  2015-06-28          1.37      89534.81     664.23   \n",
       "27             27  2015-06-21          1.27     104849.39     804.01   \n",
       "28             28  2015-06-14          1.32      89631.30     850.58   \n",
       "29             29  2015-06-07          1.07     122743.06     656.71   \n",
       "...           ...         ...           ...           ...        ...   \n",
       "18219           6  2018-02-11          1.56    1317000.47   98465.26   \n",
       "18220           7  2018-02-04          1.53    1384683.41  117922.52   \n",
       "18221           8  2018-01-28          1.61    1336979.09  118616.17   \n",
       "18222           9  2018-01-21          1.63    1283987.65  108705.28   \n",
       "18223          10  2018-01-14          1.59    1476651.08  145680.62   \n",
       "18224          11  2018-01-07          1.51    1517332.70  129541.43   \n",
       "18225           0  2018-03-25          1.60     271723.08   26996.28   \n",
       "18226           1  2018-03-18          1.73     210067.47   33437.98   \n",
       "18227           2  2018-03-11          1.63     264691.87   27566.25   \n",
       "18228           3  2018-03-04          1.46     347373.17   25990.60   \n",
       "18229           4  2018-02-25          1.49     301985.61   34200.18   \n",
       "18230           5  2018-02-18          1.64     224798.60   30149.00   \n",
       "18231           6  2018-02-11          1.47     275248.53   24732.55   \n",
       "18232           7  2018-02-04          1.41     283378.47   22474.66   \n",
       "18233           8  2018-01-28          1.80     185974.53   22918.40   \n",
       "18234           9  2018-01-21          1.83     189317.99   27049.44   \n",
       "18235          10  2018-01-14          1.82     207999.67   33869.12   \n",
       "18236          11  2018-01-07          1.48     297190.60   34734.97   \n",
       "18237           0  2018-03-25          1.62      15303.40    2325.30   \n",
       "18238           1  2018-03-18          1.56      15896.38    2055.35   \n",
       "18239           2  2018-03-11          1.56      22128.42    2162.67   \n",
       "18240           3  2018-03-04          1.54      17393.30    1832.24   \n",
       "18241           4  2018-02-25          1.57      18421.24    1974.26   \n",
       "18242           5  2018-02-18          1.56      17597.12    1892.05   \n",
       "18243           6  2018-02-11          1.57      15986.17    1924.28   \n",
       "18244           7  2018-02-04          1.63      17074.83    2046.96   \n",
       "18245           8  2018-01-28          1.71      13888.04    1191.70   \n",
       "18246           9  2018-01-21          1.87      13766.76    1191.92   \n",
       "18247          10  2018-01-14          1.93      16205.22    1527.63   \n",
       "18248          11  2018-01-07          1.62      17489.58    2894.77   \n",
       "\n",
       "            4225     4770  Total Bags  Small Bags  Large Bags  XLarge Bags  \\\n",
       "0       54454.85    48.16     8696.87     8603.62       93.25         0.00   \n",
       "1       44638.81    58.33     9505.56     9408.07       97.49         0.00   \n",
       "2      109149.67   130.50     8145.35     8042.21      103.14         0.00   \n",
       "3       71976.41    72.58     5811.16     5677.40      133.76         0.00   \n",
       "4       43838.39    75.78     6183.95     5986.26      197.69         0.00   \n",
       "5       48067.99    43.61     6683.91     6556.47      127.44         0.00   \n",
       "6       73672.72    93.26     8318.86     8196.81      122.05         0.00   \n",
       "7      101815.36    80.00     6829.22     6266.85      562.37         0.00   \n",
       "8       87315.57    85.34    11388.36    11104.53      283.83         0.00   \n",
       "9       64757.44   113.00     8625.92     8061.47      564.45         0.00   \n",
       "10      75595.85   117.07     8205.66     7877.86      327.80         0.00   \n",
       "11      52677.92   105.32    10123.90     9866.27      257.63         0.00   \n",
       "12      49880.67   101.36     8756.75     8379.98      376.77         0.00   \n",
       "13      99409.21   154.84     6034.46     5888.87      145.59         0.00   \n",
       "14      59313.12   150.50     9267.36     8489.10      778.26         0.00   \n",
       "15      65696.86   142.00     9286.68     8665.19      621.49         0.00   \n",
       "16      90062.62   240.79     7990.10     7762.87      227.23         0.00   \n",
       "17      94362.67   335.43    10306.73    10218.93       87.80         0.00   \n",
       "18      67933.79   444.78    10880.36    10745.79      134.57         0.00   \n",
       "19      68666.01   394.90    10443.22    10297.68      145.54         0.00   \n",
       "20     100961.46   368.95     9225.89     9116.34      109.55         0.00   \n",
       "21      62035.06   741.08    11847.02    11768.52       78.50         0.00   \n",
       "22      91949.05   966.61    13192.69    13061.53      131.16         0.00   \n",
       "23      82049.40  2238.02    11287.48    11103.49      183.99         0.00   \n",
       "24      94693.52  4257.64    24431.90    24290.08      108.49        33.33   \n",
       "25      72600.55  5883.16    29898.96    29663.19      235.77         0.00   \n",
       "26      57545.79  4662.71    26662.08    26311.76      350.32         0.00   \n",
       "27      76688.55  5481.18    21875.65    21662.00      213.65         0.00   \n",
       "28      55400.94  4377.19    29002.59    28343.14      659.45         0.00   \n",
       "29      99220.82    90.32    22775.21    22314.99      460.22         0.00   \n",
       "...          ...      ...         ...         ...         ...          ...   \n",
       "18219  270798.27  1839.80   945638.02   768242.42   177144.00       251.60   \n",
       "18220  287724.61  1703.52   977084.84   774695.74   201878.69       510.41   \n",
       "18221  280080.34  1270.61   936859.49   796104.27   140652.84       102.38   \n",
       "18222  259172.13  1490.02   914409.26   710654.40   203526.59       228.27   \n",
       "18223  323669.83  1580.01  1005593.78   858772.69   146808.97        12.12   \n",
       "18224  296490.29  1289.07  1089861.24   915452.78   174381.57        26.89   \n",
       "18225   77861.39   117.56   166747.85    87108.00    79495.39       144.46   \n",
       "18226   47165.54   110.40   129353.55    73163.12    56020.24       170.19   \n",
       "18227   60383.57   276.42   176465.63   107174.93    69290.70         0.00   \n",
       "18228   71213.19    79.01   250090.37    85835.17   164087.33       167.87   \n",
       "18229   49139.34    85.58   218560.51    99989.62   118314.77       256.12   \n",
       "18230   38800.64   123.13   155725.83   120428.13    35257.73        39.97   \n",
       "18231   61713.53   243.00   188559.45    88497.05    99810.80       251.60   \n",
       "18232   55360.49   133.41   205409.91    70232.59   134666.91       510.41   \n",
       "18233   33051.14    93.52   129911.47    77822.23    51986.86       102.38   \n",
       "18234   33561.32   439.47   128267.76    76091.99    51947.50       228.27   \n",
       "18235   47435.14   433.52   126261.89    89115.78    37133.99        12.12   \n",
       "18236   62967.74   157.77   199330.12   103761.55    95544.39        24.18   \n",
       "18237    2171.66     0.00    10806.44    10569.80      236.64         0.00   \n",
       "18238    1499.55     0.00    12341.48    12114.81      226.67         0.00   \n",
       "18239    3194.25     8.93    16762.57    16510.32      252.25         0.00   \n",
       "18240    1905.57     0.00    13655.49    13401.93      253.56         0.00   \n",
       "18241    2482.65     0.00    13964.33    13698.27      266.06         0.00   \n",
       "18242    1928.36     0.00    13776.71    13553.53      223.18         0.00   \n",
       "18243    1368.32     0.00    12693.57    12437.35      256.22         0.00   \n",
       "18244    1529.20     0.00    13498.67    13066.82      431.85         0.00   \n",
       "18245    3431.50     0.00     9264.84     8940.04      324.80         0.00   \n",
       "18246    2452.79   727.94     9394.11     9351.80       42.31         0.00   \n",
       "18247    2981.04   727.01    10969.54    10919.54       50.00         0.00   \n",
       "18248    2356.13   224.53    12014.15    11988.14       26.01         0.00   \n",
       "\n",
       "               type  year            region  True  \n",
       "0      conventional  2015            Albany  True  \n",
       "1      conventional  2015            Albany  True  \n",
       "2      conventional  2015            Albany  True  \n",
       "3      conventional  2015            Albany  True  \n",
       "4      conventional  2015            Albany  True  \n",
       "5      conventional  2015            Albany  True  \n",
       "6      conventional  2015            Albany  True  \n",
       "7      conventional  2015            Albany  True  \n",
       "8      conventional  2015            Albany  True  \n",
       "9      conventional  2015            Albany  True  \n",
       "10     conventional  2015            Albany  True  \n",
       "11     conventional  2015            Albany  True  \n",
       "12     conventional  2015            Albany  True  \n",
       "13     conventional  2015            Albany  True  \n",
       "14     conventional  2015            Albany  True  \n",
       "15     conventional  2015            Albany  True  \n",
       "16     conventional  2015            Albany  True  \n",
       "17     conventional  2015            Albany  True  \n",
       "18     conventional  2015            Albany  True  \n",
       "19     conventional  2015            Albany  True  \n",
       "20     conventional  2015            Albany  True  \n",
       "21     conventional  2015            Albany  True  \n",
       "22     conventional  2015            Albany  True  \n",
       "23     conventional  2015            Albany  True  \n",
       "24     conventional  2015            Albany  True  \n",
       "25     conventional  2015            Albany  True  \n",
       "26     conventional  2015            Albany  True  \n",
       "27     conventional  2015            Albany  True  \n",
       "28     conventional  2015            Albany  True  \n",
       "29     conventional  2015            Albany  True  \n",
       "...             ...   ...               ...   ...  \n",
       "18219       organic  2018           TotalUS  True  \n",
       "18220       organic  2018           TotalUS  True  \n",
       "18221       organic  2018           TotalUS  True  \n",
       "18222       organic  2018           TotalUS  True  \n",
       "18223       organic  2018           TotalUS  True  \n",
       "18224       organic  2018           TotalUS  True  \n",
       "18225       organic  2018              West  True  \n",
       "18226       organic  2018              West  True  \n",
       "18227       organic  2018              West  True  \n",
       "18228       organic  2018              West  True  \n",
       "18229       organic  2018              West  True  \n",
       "18230       organic  2018              West  True  \n",
       "18231       organic  2018              West  True  \n",
       "18232       organic  2018              West  True  \n",
       "18233       organic  2018              West  True  \n",
       "18234       organic  2018              West  True  \n",
       "18235       organic  2018              West  True  \n",
       "18236       organic  2018              West  True  \n",
       "18237       organic  2018  WestTexNewMexico  True  \n",
       "18238       organic  2018  WestTexNewMexico  True  \n",
       "18239       organic  2018  WestTexNewMexico  True  \n",
       "18240       organic  2018  WestTexNewMexico  True  \n",
       "18241       organic  2018  WestTexNewMexico  True  \n",
       "18242       organic  2018  WestTexNewMexico  True  \n",
       "18243       organic  2018  WestTexNewMexico  True  \n",
       "18244       organic  2018  WestTexNewMexico  True  \n",
       "18245       organic  2018  WestTexNewMexico  True  \n",
       "18246       organic  2018  WestTexNewMexico  True  \n",
       "18247       organic  2018  WestTexNewMexico  True  \n",
       "18248       organic  2018  WestTexNewMexico  True  \n",
       "\n",
       "[18249 rows x 15 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado[\"True\"] = True\n",
    "avocado"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To drop the column we just added, you can use **df.drop**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>1.33</td>\n",
       "      <td>64236.62</td>\n",
       "      <td>1036.74</td>\n",
       "      <td>54454.85</td>\n",
       "      <td>48.16</td>\n",
       "      <td>8696.87</td>\n",
       "      <td>8603.62</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-12-20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>54876.98</td>\n",
       "      <td>674.28</td>\n",
       "      <td>44638.81</td>\n",
       "      <td>58.33</td>\n",
       "      <td>9505.56</td>\n",
       "      <td>9408.07</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-12-13</td>\n",
       "      <td>0.93</td>\n",
       "      <td>118220.22</td>\n",
       "      <td>794.70</td>\n",
       "      <td>109149.67</td>\n",
       "      <td>130.50</td>\n",
       "      <td>8145.35</td>\n",
       "      <td>8042.21</td>\n",
       "      <td>103.14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-12-06</td>\n",
       "      <td>1.08</td>\n",
       "      <td>78992.15</td>\n",
       "      <td>1132.00</td>\n",
       "      <td>71976.41</td>\n",
       "      <td>72.58</td>\n",
       "      <td>5811.16</td>\n",
       "      <td>5677.40</td>\n",
       "      <td>133.76</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-11-29</td>\n",
       "      <td>1.28</td>\n",
       "      <td>51039.60</td>\n",
       "      <td>941.48</td>\n",
       "      <td>43838.39</td>\n",
       "      <td>75.78</td>\n",
       "      <td>6183.95</td>\n",
       "      <td>5986.26</td>\n",
       "      <td>197.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>2015-11-22</td>\n",
       "      <td>1.26</td>\n",
       "      <td>55979.78</td>\n",
       "      <td>1184.27</td>\n",
       "      <td>48067.99</td>\n",
       "      <td>43.61</td>\n",
       "      <td>6683.91</td>\n",
       "      <td>6556.47</td>\n",
       "      <td>127.44</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>2015-11-15</td>\n",
       "      <td>0.99</td>\n",
       "      <td>83453.76</td>\n",
       "      <td>1368.92</td>\n",
       "      <td>73672.72</td>\n",
       "      <td>93.26</td>\n",
       "      <td>8318.86</td>\n",
       "      <td>8196.81</td>\n",
       "      <td>122.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>2015-11-08</td>\n",
       "      <td>0.98</td>\n",
       "      <td>109428.33</td>\n",
       "      <td>703.75</td>\n",
       "      <td>101815.36</td>\n",
       "      <td>80.00</td>\n",
       "      <td>6829.22</td>\n",
       "      <td>6266.85</td>\n",
       "      <td>562.37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2015-11-01</td>\n",
       "      <td>1.02</td>\n",
       "      <td>99811.42</td>\n",
       "      <td>1022.15</td>\n",
       "      <td>87315.57</td>\n",
       "      <td>85.34</td>\n",
       "      <td>11388.36</td>\n",
       "      <td>11104.53</td>\n",
       "      <td>283.83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>2015-10-25</td>\n",
       "      <td>1.07</td>\n",
       "      <td>74338.76</td>\n",
       "      <td>842.40</td>\n",
       "      <td>64757.44</td>\n",
       "      <td>113.00</td>\n",
       "      <td>8625.92</td>\n",
       "      <td>8061.47</td>\n",
       "      <td>564.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>2015-10-18</td>\n",
       "      <td>1.12</td>\n",
       "      <td>84843.44</td>\n",
       "      <td>924.86</td>\n",
       "      <td>75595.85</td>\n",
       "      <td>117.07</td>\n",
       "      <td>8205.66</td>\n",
       "      <td>7877.86</td>\n",
       "      <td>327.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>2015-10-11</td>\n",
       "      <td>1.28</td>\n",
       "      <td>64489.17</td>\n",
       "      <td>1582.03</td>\n",
       "      <td>52677.92</td>\n",
       "      <td>105.32</td>\n",
       "      <td>10123.90</td>\n",
       "      <td>9866.27</td>\n",
       "      <td>257.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>1.31</td>\n",
       "      <td>61007.10</td>\n",
       "      <td>2268.32</td>\n",
       "      <td>49880.67</td>\n",
       "      <td>101.36</td>\n",
       "      <td>8756.75</td>\n",
       "      <td>8379.98</td>\n",
       "      <td>376.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>2015-09-27</td>\n",
       "      <td>0.99</td>\n",
       "      <td>106803.39</td>\n",
       "      <td>1204.88</td>\n",
       "      <td>99409.21</td>\n",
       "      <td>154.84</td>\n",
       "      <td>6034.46</td>\n",
       "      <td>5888.87</td>\n",
       "      <td>145.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>2015-09-20</td>\n",
       "      <td>1.33</td>\n",
       "      <td>69759.01</td>\n",
       "      <td>1028.03</td>\n",
       "      <td>59313.12</td>\n",
       "      <td>150.50</td>\n",
       "      <td>9267.36</td>\n",
       "      <td>8489.10</td>\n",
       "      <td>778.26</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>2015-09-13</td>\n",
       "      <td>1.28</td>\n",
       "      <td>76111.27</td>\n",
       "      <td>985.73</td>\n",
       "      <td>65696.86</td>\n",
       "      <td>142.00</td>\n",
       "      <td>9286.68</td>\n",
       "      <td>8665.19</td>\n",
       "      <td>621.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>2015-09-06</td>\n",
       "      <td>1.11</td>\n",
       "      <td>99172.96</td>\n",
       "      <td>879.45</td>\n",
       "      <td>90062.62</td>\n",
       "      <td>240.79</td>\n",
       "      <td>7990.10</td>\n",
       "      <td>7762.87</td>\n",
       "      <td>227.23</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>2015-08-30</td>\n",
       "      <td>1.07</td>\n",
       "      <td>105693.84</td>\n",
       "      <td>689.01</td>\n",
       "      <td>94362.67</td>\n",
       "      <td>335.43</td>\n",
       "      <td>10306.73</td>\n",
       "      <td>10218.93</td>\n",
       "      <td>87.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>2015-08-23</td>\n",
       "      <td>1.34</td>\n",
       "      <td>79992.09</td>\n",
       "      <td>733.16</td>\n",
       "      <td>67933.79</td>\n",
       "      <td>444.78</td>\n",
       "      <td>10880.36</td>\n",
       "      <td>10745.79</td>\n",
       "      <td>134.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>2015-08-16</td>\n",
       "      <td>1.33</td>\n",
       "      <td>80043.78</td>\n",
       "      <td>539.65</td>\n",
       "      <td>68666.01</td>\n",
       "      <td>394.90</td>\n",
       "      <td>10443.22</td>\n",
       "      <td>10297.68</td>\n",
       "      <td>145.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>2015-08-09</td>\n",
       "      <td>1.12</td>\n",
       "      <td>111140.93</td>\n",
       "      <td>584.63</td>\n",
       "      <td>100961.46</td>\n",
       "      <td>368.95</td>\n",
       "      <td>9225.89</td>\n",
       "      <td>9116.34</td>\n",
       "      <td>109.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>2015-08-02</td>\n",
       "      <td>1.45</td>\n",
       "      <td>75133.10</td>\n",
       "      <td>509.94</td>\n",
       "      <td>62035.06</td>\n",
       "      <td>741.08</td>\n",
       "      <td>11847.02</td>\n",
       "      <td>11768.52</td>\n",
       "      <td>78.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>2015-07-26</td>\n",
       "      <td>1.11</td>\n",
       "      <td>106757.10</td>\n",
       "      <td>648.75</td>\n",
       "      <td>91949.05</td>\n",
       "      <td>966.61</td>\n",
       "      <td>13192.69</td>\n",
       "      <td>13061.53</td>\n",
       "      <td>131.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>2015-07-19</td>\n",
       "      <td>1.26</td>\n",
       "      <td>96617.00</td>\n",
       "      <td>1042.10</td>\n",
       "      <td>82049.40</td>\n",
       "      <td>2238.02</td>\n",
       "      <td>11287.48</td>\n",
       "      <td>11103.49</td>\n",
       "      <td>183.99</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>2015-07-12</td>\n",
       "      <td>1.05</td>\n",
       "      <td>124055.31</td>\n",
       "      <td>672.25</td>\n",
       "      <td>94693.52</td>\n",
       "      <td>4257.64</td>\n",
       "      <td>24431.90</td>\n",
       "      <td>24290.08</td>\n",
       "      <td>108.49</td>\n",
       "      <td>33.33</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>2015-07-05</td>\n",
       "      <td>1.35</td>\n",
       "      <td>109252.12</td>\n",
       "      <td>869.45</td>\n",
       "      <td>72600.55</td>\n",
       "      <td>5883.16</td>\n",
       "      <td>29898.96</td>\n",
       "      <td>29663.19</td>\n",
       "      <td>235.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>2015-06-28</td>\n",
       "      <td>1.37</td>\n",
       "      <td>89534.81</td>\n",
       "      <td>664.23</td>\n",
       "      <td>57545.79</td>\n",
       "      <td>4662.71</td>\n",
       "      <td>26662.08</td>\n",
       "      <td>26311.76</td>\n",
       "      <td>350.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>2015-06-21</td>\n",
       "      <td>1.27</td>\n",
       "      <td>104849.39</td>\n",
       "      <td>804.01</td>\n",
       "      <td>76688.55</td>\n",
       "      <td>5481.18</td>\n",
       "      <td>21875.65</td>\n",
       "      <td>21662.00</td>\n",
       "      <td>213.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>2015-06-14</td>\n",
       "      <td>1.32</td>\n",
       "      <td>89631.30</td>\n",
       "      <td>850.58</td>\n",
       "      <td>55400.94</td>\n",
       "      <td>4377.19</td>\n",
       "      <td>29002.59</td>\n",
       "      <td>28343.14</td>\n",
       "      <td>659.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>2015-06-07</td>\n",
       "      <td>1.07</td>\n",
       "      <td>122743.06</td>\n",
       "      <td>656.71</td>\n",
       "      <td>99220.82</td>\n",
       "      <td>90.32</td>\n",
       "      <td>22775.21</td>\n",
       "      <td>22314.99</td>\n",
       "      <td>460.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18219</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1317000.47</td>\n",
       "      <td>98465.26</td>\n",
       "      <td>270798.27</td>\n",
       "      <td>1839.80</td>\n",
       "      <td>945638.02</td>\n",
       "      <td>768242.42</td>\n",
       "      <td>177144.00</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18220</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1384683.41</td>\n",
       "      <td>117922.52</td>\n",
       "      <td>287724.61</td>\n",
       "      <td>1703.52</td>\n",
       "      <td>977084.84</td>\n",
       "      <td>774695.74</td>\n",
       "      <td>201878.69</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18221</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.61</td>\n",
       "      <td>1336979.09</td>\n",
       "      <td>118616.17</td>\n",
       "      <td>280080.34</td>\n",
       "      <td>1270.61</td>\n",
       "      <td>936859.49</td>\n",
       "      <td>796104.27</td>\n",
       "      <td>140652.84</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18222</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1283987.65</td>\n",
       "      <td>108705.28</td>\n",
       "      <td>259172.13</td>\n",
       "      <td>1490.02</td>\n",
       "      <td>914409.26</td>\n",
       "      <td>710654.40</td>\n",
       "      <td>203526.59</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18223</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.59</td>\n",
       "      <td>1476651.08</td>\n",
       "      <td>145680.62</td>\n",
       "      <td>323669.83</td>\n",
       "      <td>1580.01</td>\n",
       "      <td>1005593.78</td>\n",
       "      <td>858772.69</td>\n",
       "      <td>146808.97</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18224</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1517332.70</td>\n",
       "      <td>129541.43</td>\n",
       "      <td>296490.29</td>\n",
       "      <td>1289.07</td>\n",
       "      <td>1089861.24</td>\n",
       "      <td>915452.78</td>\n",
       "      <td>174381.57</td>\n",
       "      <td>26.89</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18225</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.60</td>\n",
       "      <td>271723.08</td>\n",
       "      <td>26996.28</td>\n",
       "      <td>77861.39</td>\n",
       "      <td>117.56</td>\n",
       "      <td>166747.85</td>\n",
       "      <td>87108.00</td>\n",
       "      <td>79495.39</td>\n",
       "      <td>144.46</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18226</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.73</td>\n",
       "      <td>210067.47</td>\n",
       "      <td>33437.98</td>\n",
       "      <td>47165.54</td>\n",
       "      <td>110.40</td>\n",
       "      <td>129353.55</td>\n",
       "      <td>73163.12</td>\n",
       "      <td>56020.24</td>\n",
       "      <td>170.19</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18227</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.63</td>\n",
       "      <td>264691.87</td>\n",
       "      <td>27566.25</td>\n",
       "      <td>60383.57</td>\n",
       "      <td>276.42</td>\n",
       "      <td>176465.63</td>\n",
       "      <td>107174.93</td>\n",
       "      <td>69290.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18228</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.46</td>\n",
       "      <td>347373.17</td>\n",
       "      <td>25990.60</td>\n",
       "      <td>71213.19</td>\n",
       "      <td>79.01</td>\n",
       "      <td>250090.37</td>\n",
       "      <td>85835.17</td>\n",
       "      <td>164087.33</td>\n",
       "      <td>167.87</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18229</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.49</td>\n",
       "      <td>301985.61</td>\n",
       "      <td>34200.18</td>\n",
       "      <td>49139.34</td>\n",
       "      <td>85.58</td>\n",
       "      <td>218560.51</td>\n",
       "      <td>99989.62</td>\n",
       "      <td>118314.77</td>\n",
       "      <td>256.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18230</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.64</td>\n",
       "      <td>224798.60</td>\n",
       "      <td>30149.00</td>\n",
       "      <td>38800.64</td>\n",
       "      <td>123.13</td>\n",
       "      <td>155725.83</td>\n",
       "      <td>120428.13</td>\n",
       "      <td>35257.73</td>\n",
       "      <td>39.97</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18231</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.47</td>\n",
       "      <td>275248.53</td>\n",
       "      <td>24732.55</td>\n",
       "      <td>61713.53</td>\n",
       "      <td>243.00</td>\n",
       "      <td>188559.45</td>\n",
       "      <td>88497.05</td>\n",
       "      <td>99810.80</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18232</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.41</td>\n",
       "      <td>283378.47</td>\n",
       "      <td>22474.66</td>\n",
       "      <td>55360.49</td>\n",
       "      <td>133.41</td>\n",
       "      <td>205409.91</td>\n",
       "      <td>70232.59</td>\n",
       "      <td>134666.91</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18233</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.80</td>\n",
       "      <td>185974.53</td>\n",
       "      <td>22918.40</td>\n",
       "      <td>33051.14</td>\n",
       "      <td>93.52</td>\n",
       "      <td>129911.47</td>\n",
       "      <td>77822.23</td>\n",
       "      <td>51986.86</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18234</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.83</td>\n",
       "      <td>189317.99</td>\n",
       "      <td>27049.44</td>\n",
       "      <td>33561.32</td>\n",
       "      <td>439.47</td>\n",
       "      <td>128267.76</td>\n",
       "      <td>76091.99</td>\n",
       "      <td>51947.50</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18235</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.82</td>\n",
       "      <td>207999.67</td>\n",
       "      <td>33869.12</td>\n",
       "      <td>47435.14</td>\n",
       "      <td>433.52</td>\n",
       "      <td>126261.89</td>\n",
       "      <td>89115.78</td>\n",
       "      <td>37133.99</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18236</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>297190.60</td>\n",
       "      <td>34734.97</td>\n",
       "      <td>62967.74</td>\n",
       "      <td>157.77</td>\n",
       "      <td>199330.12</td>\n",
       "      <td>103761.55</td>\n",
       "      <td>95544.39</td>\n",
       "      <td>24.18</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18237</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>15303.40</td>\n",
       "      <td>2325.30</td>\n",
       "      <td>2171.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10806.44</td>\n",
       "      <td>10569.80</td>\n",
       "      <td>236.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18238</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>15896.38</td>\n",
       "      <td>2055.35</td>\n",
       "      <td>1499.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12341.48</td>\n",
       "      <td>12114.81</td>\n",
       "      <td>226.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18239</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>22128.42</td>\n",
       "      <td>2162.67</td>\n",
       "      <td>3194.25</td>\n",
       "      <td>8.93</td>\n",
       "      <td>16762.57</td>\n",
       "      <td>16510.32</td>\n",
       "      <td>252.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18240</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.54</td>\n",
       "      <td>17393.30</td>\n",
       "      <td>1832.24</td>\n",
       "      <td>1905.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13655.49</td>\n",
       "      <td>13401.93</td>\n",
       "      <td>253.56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18241</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.57</td>\n",
       "      <td>18421.24</td>\n",
       "      <td>1974.26</td>\n",
       "      <td>2482.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13964.33</td>\n",
       "      <td>13698.27</td>\n",
       "      <td>266.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18242</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>17597.12</td>\n",
       "      <td>1892.05</td>\n",
       "      <td>1928.36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13776.71</td>\n",
       "      <td>13553.53</td>\n",
       "      <td>223.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18243</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.57</td>\n",
       "      <td>15986.17</td>\n",
       "      <td>1924.28</td>\n",
       "      <td>1368.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12693.57</td>\n",
       "      <td>12437.35</td>\n",
       "      <td>256.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18244</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.63</td>\n",
       "      <td>17074.83</td>\n",
       "      <td>2046.96</td>\n",
       "      <td>1529.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13498.67</td>\n",
       "      <td>13066.82</td>\n",
       "      <td>431.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18245</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.71</td>\n",
       "      <td>13888.04</td>\n",
       "      <td>1191.70</td>\n",
       "      <td>3431.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9264.84</td>\n",
       "      <td>8940.04</td>\n",
       "      <td>324.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.87</td>\n",
       "      <td>13766.76</td>\n",
       "      <td>1191.92</td>\n",
       "      <td>2452.79</td>\n",
       "      <td>727.94</td>\n",
       "      <td>9394.11</td>\n",
       "      <td>9351.80</td>\n",
       "      <td>42.31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18247</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.93</td>\n",
       "      <td>16205.22</td>\n",
       "      <td>1527.63</td>\n",
       "      <td>2981.04</td>\n",
       "      <td>727.01</td>\n",
       "      <td>10969.54</td>\n",
       "      <td>10919.54</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18248</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.62</td>\n",
       "      <td>17489.58</td>\n",
       "      <td>2894.77</td>\n",
       "      <td>2356.13</td>\n",
       "      <td>224.53</td>\n",
       "      <td>12014.15</td>\n",
       "      <td>11988.14</td>\n",
       "      <td>26.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18249 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0        Date  AveragePrice  Total Volume       4046  \\\n",
       "0               0  2015-12-27          1.33      64236.62    1036.74   \n",
       "1               1  2015-12-20          1.35      54876.98     674.28   \n",
       "2               2  2015-12-13          0.93     118220.22     794.70   \n",
       "3               3  2015-12-06          1.08      78992.15    1132.00   \n",
       "4               4  2015-11-29          1.28      51039.60     941.48   \n",
       "5               5  2015-11-22          1.26      55979.78    1184.27   \n",
       "6               6  2015-11-15          0.99      83453.76    1368.92   \n",
       "7               7  2015-11-08          0.98     109428.33     703.75   \n",
       "8               8  2015-11-01          1.02      99811.42    1022.15   \n",
       "9               9  2015-10-25          1.07      74338.76     842.40   \n",
       "10             10  2015-10-18          1.12      84843.44     924.86   \n",
       "11             11  2015-10-11          1.28      64489.17    1582.03   \n",
       "12             12  2015-10-04          1.31      61007.10    2268.32   \n",
       "13             13  2015-09-27          0.99     106803.39    1204.88   \n",
       "14             14  2015-09-20          1.33      69759.01    1028.03   \n",
       "15             15  2015-09-13          1.28      76111.27     985.73   \n",
       "16             16  2015-09-06          1.11      99172.96     879.45   \n",
       "17             17  2015-08-30          1.07     105693.84     689.01   \n",
       "18             18  2015-08-23          1.34      79992.09     733.16   \n",
       "19             19  2015-08-16          1.33      80043.78     539.65   \n",
       "20             20  2015-08-09          1.12     111140.93     584.63   \n",
       "21             21  2015-08-02          1.45      75133.10     509.94   \n",
       "22             22  2015-07-26          1.11     106757.10     648.75   \n",
       "23             23  2015-07-19          1.26      96617.00    1042.10   \n",
       "24             24  2015-07-12          1.05     124055.31     672.25   \n",
       "25             25  2015-07-05          1.35     109252.12     869.45   \n",
       "26             26  2015-06-28          1.37      89534.81     664.23   \n",
       "27             27  2015-06-21          1.27     104849.39     804.01   \n",
       "28             28  2015-06-14          1.32      89631.30     850.58   \n",
       "29             29  2015-06-07          1.07     122743.06     656.71   \n",
       "...           ...         ...           ...           ...        ...   \n",
       "18219           6  2018-02-11          1.56    1317000.47   98465.26   \n",
       "18220           7  2018-02-04          1.53    1384683.41  117922.52   \n",
       "18221           8  2018-01-28          1.61    1336979.09  118616.17   \n",
       "18222           9  2018-01-21          1.63    1283987.65  108705.28   \n",
       "18223          10  2018-01-14          1.59    1476651.08  145680.62   \n",
       "18224          11  2018-01-07          1.51    1517332.70  129541.43   \n",
       "18225           0  2018-03-25          1.60     271723.08   26996.28   \n",
       "18226           1  2018-03-18          1.73     210067.47   33437.98   \n",
       "18227           2  2018-03-11          1.63     264691.87   27566.25   \n",
       "18228           3  2018-03-04          1.46     347373.17   25990.60   \n",
       "18229           4  2018-02-25          1.49     301985.61   34200.18   \n",
       "18230           5  2018-02-18          1.64     224798.60   30149.00   \n",
       "18231           6  2018-02-11          1.47     275248.53   24732.55   \n",
       "18232           7  2018-02-04          1.41     283378.47   22474.66   \n",
       "18233           8  2018-01-28          1.80     185974.53   22918.40   \n",
       "18234           9  2018-01-21          1.83     189317.99   27049.44   \n",
       "18235          10  2018-01-14          1.82     207999.67   33869.12   \n",
       "18236          11  2018-01-07          1.48     297190.60   34734.97   \n",
       "18237           0  2018-03-25          1.62      15303.40    2325.30   \n",
       "18238           1  2018-03-18          1.56      15896.38    2055.35   \n",
       "18239           2  2018-03-11          1.56      22128.42    2162.67   \n",
       "18240           3  2018-03-04          1.54      17393.30    1832.24   \n",
       "18241           4  2018-02-25          1.57      18421.24    1974.26   \n",
       "18242           5  2018-02-18          1.56      17597.12    1892.05   \n",
       "18243           6  2018-02-11          1.57      15986.17    1924.28   \n",
       "18244           7  2018-02-04          1.63      17074.83    2046.96   \n",
       "18245           8  2018-01-28          1.71      13888.04    1191.70   \n",
       "18246           9  2018-01-21          1.87      13766.76    1191.92   \n",
       "18247          10  2018-01-14          1.93      16205.22    1527.63   \n",
       "18248          11  2018-01-07          1.62      17489.58    2894.77   \n",
       "\n",
       "            4225     4770  Total Bags  Small Bags  Large Bags  XLarge Bags  \\\n",
       "0       54454.85    48.16     8696.87     8603.62       93.25         0.00   \n",
       "1       44638.81    58.33     9505.56     9408.07       97.49         0.00   \n",
       "2      109149.67   130.50     8145.35     8042.21      103.14         0.00   \n",
       "3       71976.41    72.58     5811.16     5677.40      133.76         0.00   \n",
       "4       43838.39    75.78     6183.95     5986.26      197.69         0.00   \n",
       "5       48067.99    43.61     6683.91     6556.47      127.44         0.00   \n",
       "6       73672.72    93.26     8318.86     8196.81      122.05         0.00   \n",
       "7      101815.36    80.00     6829.22     6266.85      562.37         0.00   \n",
       "8       87315.57    85.34    11388.36    11104.53      283.83         0.00   \n",
       "9       64757.44   113.00     8625.92     8061.47      564.45         0.00   \n",
       "10      75595.85   117.07     8205.66     7877.86      327.80         0.00   \n",
       "11      52677.92   105.32    10123.90     9866.27      257.63         0.00   \n",
       "12      49880.67   101.36     8756.75     8379.98      376.77         0.00   \n",
       "13      99409.21   154.84     6034.46     5888.87      145.59         0.00   \n",
       "14      59313.12   150.50     9267.36     8489.10      778.26         0.00   \n",
       "15      65696.86   142.00     9286.68     8665.19      621.49         0.00   \n",
       "16      90062.62   240.79     7990.10     7762.87      227.23         0.00   \n",
       "17      94362.67   335.43    10306.73    10218.93       87.80         0.00   \n",
       "18      67933.79   444.78    10880.36    10745.79      134.57         0.00   \n",
       "19      68666.01   394.90    10443.22    10297.68      145.54         0.00   \n",
       "20     100961.46   368.95     9225.89     9116.34      109.55         0.00   \n",
       "21      62035.06   741.08    11847.02    11768.52       78.50         0.00   \n",
       "22      91949.05   966.61    13192.69    13061.53      131.16         0.00   \n",
       "23      82049.40  2238.02    11287.48    11103.49      183.99         0.00   \n",
       "24      94693.52  4257.64    24431.90    24290.08      108.49        33.33   \n",
       "25      72600.55  5883.16    29898.96    29663.19      235.77         0.00   \n",
       "26      57545.79  4662.71    26662.08    26311.76      350.32         0.00   \n",
       "27      76688.55  5481.18    21875.65    21662.00      213.65         0.00   \n",
       "28      55400.94  4377.19    29002.59    28343.14      659.45         0.00   \n",
       "29      99220.82    90.32    22775.21    22314.99      460.22         0.00   \n",
       "...          ...      ...         ...         ...         ...          ...   \n",
       "18219  270798.27  1839.80   945638.02   768242.42   177144.00       251.60   \n",
       "18220  287724.61  1703.52   977084.84   774695.74   201878.69       510.41   \n",
       "18221  280080.34  1270.61   936859.49   796104.27   140652.84       102.38   \n",
       "18222  259172.13  1490.02   914409.26   710654.40   203526.59       228.27   \n",
       "18223  323669.83  1580.01  1005593.78   858772.69   146808.97        12.12   \n",
       "18224  296490.29  1289.07  1089861.24   915452.78   174381.57        26.89   \n",
       "18225   77861.39   117.56   166747.85    87108.00    79495.39       144.46   \n",
       "18226   47165.54   110.40   129353.55    73163.12    56020.24       170.19   \n",
       "18227   60383.57   276.42   176465.63   107174.93    69290.70         0.00   \n",
       "18228   71213.19    79.01   250090.37    85835.17   164087.33       167.87   \n",
       "18229   49139.34    85.58   218560.51    99989.62   118314.77       256.12   \n",
       "18230   38800.64   123.13   155725.83   120428.13    35257.73        39.97   \n",
       "18231   61713.53   243.00   188559.45    88497.05    99810.80       251.60   \n",
       "18232   55360.49   133.41   205409.91    70232.59   134666.91       510.41   \n",
       "18233   33051.14    93.52   129911.47    77822.23    51986.86       102.38   \n",
       "18234   33561.32   439.47   128267.76    76091.99    51947.50       228.27   \n",
       "18235   47435.14   433.52   126261.89    89115.78    37133.99        12.12   \n",
       "18236   62967.74   157.77   199330.12   103761.55    95544.39        24.18   \n",
       "18237    2171.66     0.00    10806.44    10569.80      236.64         0.00   \n",
       "18238    1499.55     0.00    12341.48    12114.81      226.67         0.00   \n",
       "18239    3194.25     8.93    16762.57    16510.32      252.25         0.00   \n",
       "18240    1905.57     0.00    13655.49    13401.93      253.56         0.00   \n",
       "18241    2482.65     0.00    13964.33    13698.27      266.06         0.00   \n",
       "18242    1928.36     0.00    13776.71    13553.53      223.18         0.00   \n",
       "18243    1368.32     0.00    12693.57    12437.35      256.22         0.00   \n",
       "18244    1529.20     0.00    13498.67    13066.82      431.85         0.00   \n",
       "18245    3431.50     0.00     9264.84     8940.04      324.80         0.00   \n",
       "18246    2452.79   727.94     9394.11     9351.80       42.31         0.00   \n",
       "18247    2981.04   727.01    10969.54    10919.54       50.00         0.00   \n",
       "18248    2356.13   224.53    12014.15    11988.14       26.01         0.00   \n",
       "\n",
       "               type  year            region  \n",
       "0      conventional  2015            Albany  \n",
       "1      conventional  2015            Albany  \n",
       "2      conventional  2015            Albany  \n",
       "3      conventional  2015            Albany  \n",
       "4      conventional  2015            Albany  \n",
       "5      conventional  2015            Albany  \n",
       "6      conventional  2015            Albany  \n",
       "7      conventional  2015            Albany  \n",
       "8      conventional  2015            Albany  \n",
       "9      conventional  2015            Albany  \n",
       "10     conventional  2015            Albany  \n",
       "11     conventional  2015            Albany  \n",
       "12     conventional  2015            Albany  \n",
       "13     conventional  2015            Albany  \n",
       "14     conventional  2015            Albany  \n",
       "15     conventional  2015            Albany  \n",
       "16     conventional  2015            Albany  \n",
       "17     conventional  2015            Albany  \n",
       "18     conventional  2015            Albany  \n",
       "19     conventional  2015            Albany  \n",
       "20     conventional  2015            Albany  \n",
       "21     conventional  2015            Albany  \n",
       "22     conventional  2015            Albany  \n",
       "23     conventional  2015            Albany  \n",
       "24     conventional  2015            Albany  \n",
       "25     conventional  2015            Albany  \n",
       "26     conventional  2015            Albany  \n",
       "27     conventional  2015            Albany  \n",
       "28     conventional  2015            Albany  \n",
       "29     conventional  2015            Albany  \n",
       "...             ...   ...               ...  \n",
       "18219       organic  2018           TotalUS  \n",
       "18220       organic  2018           TotalUS  \n",
       "18221       organic  2018           TotalUS  \n",
       "18222       organic  2018           TotalUS  \n",
       "18223       organic  2018           TotalUS  \n",
       "18224       organic  2018           TotalUS  \n",
       "18225       organic  2018              West  \n",
       "18226       organic  2018              West  \n",
       "18227       organic  2018              West  \n",
       "18228       organic  2018              West  \n",
       "18229       organic  2018              West  \n",
       "18230       organic  2018              West  \n",
       "18231       organic  2018              West  \n",
       "18232       organic  2018              West  \n",
       "18233       organic  2018              West  \n",
       "18234       organic  2018              West  \n",
       "18235       organic  2018              West  \n",
       "18236       organic  2018              West  \n",
       "18237       organic  2018  WestTexNewMexico  \n",
       "18238       organic  2018  WestTexNewMexico  \n",
       "18239       organic  2018  WestTexNewMexico  \n",
       "18240       organic  2018  WestTexNewMexico  \n",
       "18241       organic  2018  WestTexNewMexico  \n",
       "18242       organic  2018  WestTexNewMexico  \n",
       "18243       organic  2018  WestTexNewMexico  \n",
       "18244       organic  2018  WestTexNewMexico  \n",
       "18245       organic  2018  WestTexNewMexico  \n",
       "18246       organic  2018  WestTexNewMexico  \n",
       "18247       organic  2018  WestTexNewMexico  \n",
       "18248       organic  2018  WestTexNewMexico  \n",
       "\n",
       "[18249 rows x 14 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado = avocado.drop(columns=[\"True\"])\n",
    "avocado"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we wanted to include a new column in our dataframe? For example, what if we wanted to create a column called **Conventional** and have the value be True if the avocado type is conventional and false if it wasn't.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "      <th>Conventional</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>1.33</td>\n",
       "      <td>64236.62</td>\n",
       "      <td>1036.74</td>\n",
       "      <td>54454.85</td>\n",
       "      <td>48.16</td>\n",
       "      <td>8696.87</td>\n",
       "      <td>8603.62</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-12-20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>54876.98</td>\n",
       "      <td>674.28</td>\n",
       "      <td>44638.81</td>\n",
       "      <td>58.33</td>\n",
       "      <td>9505.56</td>\n",
       "      <td>9408.07</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-12-13</td>\n",
       "      <td>0.93</td>\n",
       "      <td>118220.22</td>\n",
       "      <td>794.70</td>\n",
       "      <td>109149.67</td>\n",
       "      <td>130.50</td>\n",
       "      <td>8145.35</td>\n",
       "      <td>8042.21</td>\n",
       "      <td>103.14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-12-06</td>\n",
       "      <td>1.08</td>\n",
       "      <td>78992.15</td>\n",
       "      <td>1132.00</td>\n",
       "      <td>71976.41</td>\n",
       "      <td>72.58</td>\n",
       "      <td>5811.16</td>\n",
       "      <td>5677.40</td>\n",
       "      <td>133.76</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-11-29</td>\n",
       "      <td>1.28</td>\n",
       "      <td>51039.60</td>\n",
       "      <td>941.48</td>\n",
       "      <td>43838.39</td>\n",
       "      <td>75.78</td>\n",
       "      <td>6183.95</td>\n",
       "      <td>5986.26</td>\n",
       "      <td>197.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>2015-11-22</td>\n",
       "      <td>1.26</td>\n",
       "      <td>55979.78</td>\n",
       "      <td>1184.27</td>\n",
       "      <td>48067.99</td>\n",
       "      <td>43.61</td>\n",
       "      <td>6683.91</td>\n",
       "      <td>6556.47</td>\n",
       "      <td>127.44</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>2015-11-15</td>\n",
       "      <td>0.99</td>\n",
       "      <td>83453.76</td>\n",
       "      <td>1368.92</td>\n",
       "      <td>73672.72</td>\n",
       "      <td>93.26</td>\n",
       "      <td>8318.86</td>\n",
       "      <td>8196.81</td>\n",
       "      <td>122.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>2015-11-08</td>\n",
       "      <td>0.98</td>\n",
       "      <td>109428.33</td>\n",
       "      <td>703.75</td>\n",
       "      <td>101815.36</td>\n",
       "      <td>80.00</td>\n",
       "      <td>6829.22</td>\n",
       "      <td>6266.85</td>\n",
       "      <td>562.37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>2015-11-01</td>\n",
       "      <td>1.02</td>\n",
       "      <td>99811.42</td>\n",
       "      <td>1022.15</td>\n",
       "      <td>87315.57</td>\n",
       "      <td>85.34</td>\n",
       "      <td>11388.36</td>\n",
       "      <td>11104.53</td>\n",
       "      <td>283.83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>2015-10-25</td>\n",
       "      <td>1.07</td>\n",
       "      <td>74338.76</td>\n",
       "      <td>842.40</td>\n",
       "      <td>64757.44</td>\n",
       "      <td>113.00</td>\n",
       "      <td>8625.92</td>\n",
       "      <td>8061.47</td>\n",
       "      <td>564.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>2015-10-18</td>\n",
       "      <td>1.12</td>\n",
       "      <td>84843.44</td>\n",
       "      <td>924.86</td>\n",
       "      <td>75595.85</td>\n",
       "      <td>117.07</td>\n",
       "      <td>8205.66</td>\n",
       "      <td>7877.86</td>\n",
       "      <td>327.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>2015-10-11</td>\n",
       "      <td>1.28</td>\n",
       "      <td>64489.17</td>\n",
       "      <td>1582.03</td>\n",
       "      <td>52677.92</td>\n",
       "      <td>105.32</td>\n",
       "      <td>10123.90</td>\n",
       "      <td>9866.27</td>\n",
       "      <td>257.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>2015-10-04</td>\n",
       "      <td>1.31</td>\n",
       "      <td>61007.10</td>\n",
       "      <td>2268.32</td>\n",
       "      <td>49880.67</td>\n",
       "      <td>101.36</td>\n",
       "      <td>8756.75</td>\n",
       "      <td>8379.98</td>\n",
       "      <td>376.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>2015-09-27</td>\n",
       "      <td>0.99</td>\n",
       "      <td>106803.39</td>\n",
       "      <td>1204.88</td>\n",
       "      <td>99409.21</td>\n",
       "      <td>154.84</td>\n",
       "      <td>6034.46</td>\n",
       "      <td>5888.87</td>\n",
       "      <td>145.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>2015-09-20</td>\n",
       "      <td>1.33</td>\n",
       "      <td>69759.01</td>\n",
       "      <td>1028.03</td>\n",
       "      <td>59313.12</td>\n",
       "      <td>150.50</td>\n",
       "      <td>9267.36</td>\n",
       "      <td>8489.10</td>\n",
       "      <td>778.26</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>2015-09-13</td>\n",
       "      <td>1.28</td>\n",
       "      <td>76111.27</td>\n",
       "      <td>985.73</td>\n",
       "      <td>65696.86</td>\n",
       "      <td>142.00</td>\n",
       "      <td>9286.68</td>\n",
       "      <td>8665.19</td>\n",
       "      <td>621.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>2015-09-06</td>\n",
       "      <td>1.11</td>\n",
       "      <td>99172.96</td>\n",
       "      <td>879.45</td>\n",
       "      <td>90062.62</td>\n",
       "      <td>240.79</td>\n",
       "      <td>7990.10</td>\n",
       "      <td>7762.87</td>\n",
       "      <td>227.23</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>2015-08-30</td>\n",
       "      <td>1.07</td>\n",
       "      <td>105693.84</td>\n",
       "      <td>689.01</td>\n",
       "      <td>94362.67</td>\n",
       "      <td>335.43</td>\n",
       "      <td>10306.73</td>\n",
       "      <td>10218.93</td>\n",
       "      <td>87.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>2015-08-23</td>\n",
       "      <td>1.34</td>\n",
       "      <td>79992.09</td>\n",
       "      <td>733.16</td>\n",
       "      <td>67933.79</td>\n",
       "      <td>444.78</td>\n",
       "      <td>10880.36</td>\n",
       "      <td>10745.79</td>\n",
       "      <td>134.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>2015-08-16</td>\n",
       "      <td>1.33</td>\n",
       "      <td>80043.78</td>\n",
       "      <td>539.65</td>\n",
       "      <td>68666.01</td>\n",
       "      <td>394.90</td>\n",
       "      <td>10443.22</td>\n",
       "      <td>10297.68</td>\n",
       "      <td>145.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>2015-08-09</td>\n",
       "      <td>1.12</td>\n",
       "      <td>111140.93</td>\n",
       "      <td>584.63</td>\n",
       "      <td>100961.46</td>\n",
       "      <td>368.95</td>\n",
       "      <td>9225.89</td>\n",
       "      <td>9116.34</td>\n",
       "      <td>109.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>2015-08-02</td>\n",
       "      <td>1.45</td>\n",
       "      <td>75133.10</td>\n",
       "      <td>509.94</td>\n",
       "      <td>62035.06</td>\n",
       "      <td>741.08</td>\n",
       "      <td>11847.02</td>\n",
       "      <td>11768.52</td>\n",
       "      <td>78.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>2015-07-26</td>\n",
       "      <td>1.11</td>\n",
       "      <td>106757.10</td>\n",
       "      <td>648.75</td>\n",
       "      <td>91949.05</td>\n",
       "      <td>966.61</td>\n",
       "      <td>13192.69</td>\n",
       "      <td>13061.53</td>\n",
       "      <td>131.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>2015-07-19</td>\n",
       "      <td>1.26</td>\n",
       "      <td>96617.00</td>\n",
       "      <td>1042.10</td>\n",
       "      <td>82049.40</td>\n",
       "      <td>2238.02</td>\n",
       "      <td>11287.48</td>\n",
       "      <td>11103.49</td>\n",
       "      <td>183.99</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>2015-07-12</td>\n",
       "      <td>1.05</td>\n",
       "      <td>124055.31</td>\n",
       "      <td>672.25</td>\n",
       "      <td>94693.52</td>\n",
       "      <td>4257.64</td>\n",
       "      <td>24431.90</td>\n",
       "      <td>24290.08</td>\n",
       "      <td>108.49</td>\n",
       "      <td>33.33</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>2015-07-05</td>\n",
       "      <td>1.35</td>\n",
       "      <td>109252.12</td>\n",
       "      <td>869.45</td>\n",
       "      <td>72600.55</td>\n",
       "      <td>5883.16</td>\n",
       "      <td>29898.96</td>\n",
       "      <td>29663.19</td>\n",
       "      <td>235.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>2015-06-28</td>\n",
       "      <td>1.37</td>\n",
       "      <td>89534.81</td>\n",
       "      <td>664.23</td>\n",
       "      <td>57545.79</td>\n",
       "      <td>4662.71</td>\n",
       "      <td>26662.08</td>\n",
       "      <td>26311.76</td>\n",
       "      <td>350.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>2015-06-21</td>\n",
       "      <td>1.27</td>\n",
       "      <td>104849.39</td>\n",
       "      <td>804.01</td>\n",
       "      <td>76688.55</td>\n",
       "      <td>5481.18</td>\n",
       "      <td>21875.65</td>\n",
       "      <td>21662.00</td>\n",
       "      <td>213.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>2015-06-14</td>\n",
       "      <td>1.32</td>\n",
       "      <td>89631.30</td>\n",
       "      <td>850.58</td>\n",
       "      <td>55400.94</td>\n",
       "      <td>4377.19</td>\n",
       "      <td>29002.59</td>\n",
       "      <td>28343.14</td>\n",
       "      <td>659.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>2015-06-07</td>\n",
       "      <td>1.07</td>\n",
       "      <td>122743.06</td>\n",
       "      <td>656.71</td>\n",
       "      <td>99220.82</td>\n",
       "      <td>90.32</td>\n",
       "      <td>22775.21</td>\n",
       "      <td>22314.99</td>\n",
       "      <td>460.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18219</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>1317000.47</td>\n",
       "      <td>98465.26</td>\n",
       "      <td>270798.27</td>\n",
       "      <td>1839.80</td>\n",
       "      <td>945638.02</td>\n",
       "      <td>768242.42</td>\n",
       "      <td>177144.00</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18220</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.53</td>\n",
       "      <td>1384683.41</td>\n",
       "      <td>117922.52</td>\n",
       "      <td>287724.61</td>\n",
       "      <td>1703.52</td>\n",
       "      <td>977084.84</td>\n",
       "      <td>774695.74</td>\n",
       "      <td>201878.69</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18221</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.61</td>\n",
       "      <td>1336979.09</td>\n",
       "      <td>118616.17</td>\n",
       "      <td>280080.34</td>\n",
       "      <td>1270.61</td>\n",
       "      <td>936859.49</td>\n",
       "      <td>796104.27</td>\n",
       "      <td>140652.84</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18222</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1283987.65</td>\n",
       "      <td>108705.28</td>\n",
       "      <td>259172.13</td>\n",
       "      <td>1490.02</td>\n",
       "      <td>914409.26</td>\n",
       "      <td>710654.40</td>\n",
       "      <td>203526.59</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18223</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.59</td>\n",
       "      <td>1476651.08</td>\n",
       "      <td>145680.62</td>\n",
       "      <td>323669.83</td>\n",
       "      <td>1580.01</td>\n",
       "      <td>1005593.78</td>\n",
       "      <td>858772.69</td>\n",
       "      <td>146808.97</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18224</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.51</td>\n",
       "      <td>1517332.70</td>\n",
       "      <td>129541.43</td>\n",
       "      <td>296490.29</td>\n",
       "      <td>1289.07</td>\n",
       "      <td>1089861.24</td>\n",
       "      <td>915452.78</td>\n",
       "      <td>174381.57</td>\n",
       "      <td>26.89</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>TotalUS</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18225</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.60</td>\n",
       "      <td>271723.08</td>\n",
       "      <td>26996.28</td>\n",
       "      <td>77861.39</td>\n",
       "      <td>117.56</td>\n",
       "      <td>166747.85</td>\n",
       "      <td>87108.00</td>\n",
       "      <td>79495.39</td>\n",
       "      <td>144.46</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18226</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.73</td>\n",
       "      <td>210067.47</td>\n",
       "      <td>33437.98</td>\n",
       "      <td>47165.54</td>\n",
       "      <td>110.40</td>\n",
       "      <td>129353.55</td>\n",
       "      <td>73163.12</td>\n",
       "      <td>56020.24</td>\n",
       "      <td>170.19</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18227</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.63</td>\n",
       "      <td>264691.87</td>\n",
       "      <td>27566.25</td>\n",
       "      <td>60383.57</td>\n",
       "      <td>276.42</td>\n",
       "      <td>176465.63</td>\n",
       "      <td>107174.93</td>\n",
       "      <td>69290.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18228</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.46</td>\n",
       "      <td>347373.17</td>\n",
       "      <td>25990.60</td>\n",
       "      <td>71213.19</td>\n",
       "      <td>79.01</td>\n",
       "      <td>250090.37</td>\n",
       "      <td>85835.17</td>\n",
       "      <td>164087.33</td>\n",
       "      <td>167.87</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18229</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.49</td>\n",
       "      <td>301985.61</td>\n",
       "      <td>34200.18</td>\n",
       "      <td>49139.34</td>\n",
       "      <td>85.58</td>\n",
       "      <td>218560.51</td>\n",
       "      <td>99989.62</td>\n",
       "      <td>118314.77</td>\n",
       "      <td>256.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18230</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.64</td>\n",
       "      <td>224798.60</td>\n",
       "      <td>30149.00</td>\n",
       "      <td>38800.64</td>\n",
       "      <td>123.13</td>\n",
       "      <td>155725.83</td>\n",
       "      <td>120428.13</td>\n",
       "      <td>35257.73</td>\n",
       "      <td>39.97</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18231</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.47</td>\n",
       "      <td>275248.53</td>\n",
       "      <td>24732.55</td>\n",
       "      <td>61713.53</td>\n",
       "      <td>243.00</td>\n",
       "      <td>188559.45</td>\n",
       "      <td>88497.05</td>\n",
       "      <td>99810.80</td>\n",
       "      <td>251.60</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18232</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.41</td>\n",
       "      <td>283378.47</td>\n",
       "      <td>22474.66</td>\n",
       "      <td>55360.49</td>\n",
       "      <td>133.41</td>\n",
       "      <td>205409.91</td>\n",
       "      <td>70232.59</td>\n",
       "      <td>134666.91</td>\n",
       "      <td>510.41</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18233</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.80</td>\n",
       "      <td>185974.53</td>\n",
       "      <td>22918.40</td>\n",
       "      <td>33051.14</td>\n",
       "      <td>93.52</td>\n",
       "      <td>129911.47</td>\n",
       "      <td>77822.23</td>\n",
       "      <td>51986.86</td>\n",
       "      <td>102.38</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18234</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.83</td>\n",
       "      <td>189317.99</td>\n",
       "      <td>27049.44</td>\n",
       "      <td>33561.32</td>\n",
       "      <td>439.47</td>\n",
       "      <td>128267.76</td>\n",
       "      <td>76091.99</td>\n",
       "      <td>51947.50</td>\n",
       "      <td>228.27</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18235</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.82</td>\n",
       "      <td>207999.67</td>\n",
       "      <td>33869.12</td>\n",
       "      <td>47435.14</td>\n",
       "      <td>433.52</td>\n",
       "      <td>126261.89</td>\n",
       "      <td>89115.78</td>\n",
       "      <td>37133.99</td>\n",
       "      <td>12.12</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18236</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.48</td>\n",
       "      <td>297190.60</td>\n",
       "      <td>34734.97</td>\n",
       "      <td>62967.74</td>\n",
       "      <td>157.77</td>\n",
       "      <td>199330.12</td>\n",
       "      <td>103761.55</td>\n",
       "      <td>95544.39</td>\n",
       "      <td>24.18</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>West</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18237</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-03-25</td>\n",
       "      <td>1.62</td>\n",
       "      <td>15303.40</td>\n",
       "      <td>2325.30</td>\n",
       "      <td>2171.66</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10806.44</td>\n",
       "      <td>10569.80</td>\n",
       "      <td>236.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18238</th>\n",
       "      <td>1</td>\n",
       "      <td>2018-03-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>15896.38</td>\n",
       "      <td>2055.35</td>\n",
       "      <td>1499.55</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12341.48</td>\n",
       "      <td>12114.81</td>\n",
       "      <td>226.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18239</th>\n",
       "      <td>2</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1.56</td>\n",
       "      <td>22128.42</td>\n",
       "      <td>2162.67</td>\n",
       "      <td>3194.25</td>\n",
       "      <td>8.93</td>\n",
       "      <td>16762.57</td>\n",
       "      <td>16510.32</td>\n",
       "      <td>252.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18240</th>\n",
       "      <td>3</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>1.54</td>\n",
       "      <td>17393.30</td>\n",
       "      <td>1832.24</td>\n",
       "      <td>1905.57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13655.49</td>\n",
       "      <td>13401.93</td>\n",
       "      <td>253.56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18241</th>\n",
       "      <td>4</td>\n",
       "      <td>2018-02-25</td>\n",
       "      <td>1.57</td>\n",
       "      <td>18421.24</td>\n",
       "      <td>1974.26</td>\n",
       "      <td>2482.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13964.33</td>\n",
       "      <td>13698.27</td>\n",
       "      <td>266.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18242</th>\n",
       "      <td>5</td>\n",
       "      <td>2018-02-18</td>\n",
       "      <td>1.56</td>\n",
       "      <td>17597.12</td>\n",
       "      <td>1892.05</td>\n",
       "      <td>1928.36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13776.71</td>\n",
       "      <td>13553.53</td>\n",
       "      <td>223.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18243</th>\n",
       "      <td>6</td>\n",
       "      <td>2018-02-11</td>\n",
       "      <td>1.57</td>\n",
       "      <td>15986.17</td>\n",
       "      <td>1924.28</td>\n",
       "      <td>1368.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12693.57</td>\n",
       "      <td>12437.35</td>\n",
       "      <td>256.22</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18244</th>\n",
       "      <td>7</td>\n",
       "      <td>2018-02-04</td>\n",
       "      <td>1.63</td>\n",
       "      <td>17074.83</td>\n",
       "      <td>2046.96</td>\n",
       "      <td>1529.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>13498.67</td>\n",
       "      <td>13066.82</td>\n",
       "      <td>431.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18245</th>\n",
       "      <td>8</td>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>1.71</td>\n",
       "      <td>13888.04</td>\n",
       "      <td>1191.70</td>\n",
       "      <td>3431.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9264.84</td>\n",
       "      <td>8940.04</td>\n",
       "      <td>324.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>9</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>1.87</td>\n",
       "      <td>13766.76</td>\n",
       "      <td>1191.92</td>\n",
       "      <td>2452.79</td>\n",
       "      <td>727.94</td>\n",
       "      <td>9394.11</td>\n",
       "      <td>9351.80</td>\n",
       "      <td>42.31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18247</th>\n",
       "      <td>10</td>\n",
       "      <td>2018-01-14</td>\n",
       "      <td>1.93</td>\n",
       "      <td>16205.22</td>\n",
       "      <td>1527.63</td>\n",
       "      <td>2981.04</td>\n",
       "      <td>727.01</td>\n",
       "      <td>10969.54</td>\n",
       "      <td>10919.54</td>\n",
       "      <td>50.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18248</th>\n",
       "      <td>11</td>\n",
       "      <td>2018-01-07</td>\n",
       "      <td>1.62</td>\n",
       "      <td>17489.58</td>\n",
       "      <td>2894.77</td>\n",
       "      <td>2356.13</td>\n",
       "      <td>224.53</td>\n",
       "      <td>12014.15</td>\n",
       "      <td>11988.14</td>\n",
       "      <td>26.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>organic</td>\n",
       "      <td>2018</td>\n",
       "      <td>WestTexNewMexico</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18249 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0        Date  AveragePrice  Total Volume       4046  \\\n",
       "0               0  2015-12-27          1.33      64236.62    1036.74   \n",
       "1               1  2015-12-20          1.35      54876.98     674.28   \n",
       "2               2  2015-12-13          0.93     118220.22     794.70   \n",
       "3               3  2015-12-06          1.08      78992.15    1132.00   \n",
       "4               4  2015-11-29          1.28      51039.60     941.48   \n",
       "5               5  2015-11-22          1.26      55979.78    1184.27   \n",
       "6               6  2015-11-15          0.99      83453.76    1368.92   \n",
       "7               7  2015-11-08          0.98     109428.33     703.75   \n",
       "8               8  2015-11-01          1.02      99811.42    1022.15   \n",
       "9               9  2015-10-25          1.07      74338.76     842.40   \n",
       "10             10  2015-10-18          1.12      84843.44     924.86   \n",
       "11             11  2015-10-11          1.28      64489.17    1582.03   \n",
       "12             12  2015-10-04          1.31      61007.10    2268.32   \n",
       "13             13  2015-09-27          0.99     106803.39    1204.88   \n",
       "14             14  2015-09-20          1.33      69759.01    1028.03   \n",
       "15             15  2015-09-13          1.28      76111.27     985.73   \n",
       "16             16  2015-09-06          1.11      99172.96     879.45   \n",
       "17             17  2015-08-30          1.07     105693.84     689.01   \n",
       "18             18  2015-08-23          1.34      79992.09     733.16   \n",
       "19             19  2015-08-16          1.33      80043.78     539.65   \n",
       "20             20  2015-08-09          1.12     111140.93     584.63   \n",
       "21             21  2015-08-02          1.45      75133.10     509.94   \n",
       "22             22  2015-07-26          1.11     106757.10     648.75   \n",
       "23             23  2015-07-19          1.26      96617.00    1042.10   \n",
       "24             24  2015-07-12          1.05     124055.31     672.25   \n",
       "25             25  2015-07-05          1.35     109252.12     869.45   \n",
       "26             26  2015-06-28          1.37      89534.81     664.23   \n",
       "27             27  2015-06-21          1.27     104849.39     804.01   \n",
       "28             28  2015-06-14          1.32      89631.30     850.58   \n",
       "29             29  2015-06-07          1.07     122743.06     656.71   \n",
       "...           ...         ...           ...           ...        ...   \n",
       "18219           6  2018-02-11          1.56    1317000.47   98465.26   \n",
       "18220           7  2018-02-04          1.53    1384683.41  117922.52   \n",
       "18221           8  2018-01-28          1.61    1336979.09  118616.17   \n",
       "18222           9  2018-01-21          1.63    1283987.65  108705.28   \n",
       "18223          10  2018-01-14          1.59    1476651.08  145680.62   \n",
       "18224          11  2018-01-07          1.51    1517332.70  129541.43   \n",
       "18225           0  2018-03-25          1.60     271723.08   26996.28   \n",
       "18226           1  2018-03-18          1.73     210067.47   33437.98   \n",
       "18227           2  2018-03-11          1.63     264691.87   27566.25   \n",
       "18228           3  2018-03-04          1.46     347373.17   25990.60   \n",
       "18229           4  2018-02-25          1.49     301985.61   34200.18   \n",
       "18230           5  2018-02-18          1.64     224798.60   30149.00   \n",
       "18231           6  2018-02-11          1.47     275248.53   24732.55   \n",
       "18232           7  2018-02-04          1.41     283378.47   22474.66   \n",
       "18233           8  2018-01-28          1.80     185974.53   22918.40   \n",
       "18234           9  2018-01-21          1.83     189317.99   27049.44   \n",
       "18235          10  2018-01-14          1.82     207999.67   33869.12   \n",
       "18236          11  2018-01-07          1.48     297190.60   34734.97   \n",
       "18237           0  2018-03-25          1.62      15303.40    2325.30   \n",
       "18238           1  2018-03-18          1.56      15896.38    2055.35   \n",
       "18239           2  2018-03-11          1.56      22128.42    2162.67   \n",
       "18240           3  2018-03-04          1.54      17393.30    1832.24   \n",
       "18241           4  2018-02-25          1.57      18421.24    1974.26   \n",
       "18242           5  2018-02-18          1.56      17597.12    1892.05   \n",
       "18243           6  2018-02-11          1.57      15986.17    1924.28   \n",
       "18244           7  2018-02-04          1.63      17074.83    2046.96   \n",
       "18245           8  2018-01-28          1.71      13888.04    1191.70   \n",
       "18246           9  2018-01-21          1.87      13766.76    1191.92   \n",
       "18247          10  2018-01-14          1.93      16205.22    1527.63   \n",
       "18248          11  2018-01-07          1.62      17489.58    2894.77   \n",
       "\n",
       "            4225     4770  Total Bags  Small Bags  Large Bags  XLarge Bags  \\\n",
       "0       54454.85    48.16     8696.87     8603.62       93.25         0.00   \n",
       "1       44638.81    58.33     9505.56     9408.07       97.49         0.00   \n",
       "2      109149.67   130.50     8145.35     8042.21      103.14         0.00   \n",
       "3       71976.41    72.58     5811.16     5677.40      133.76         0.00   \n",
       "4       43838.39    75.78     6183.95     5986.26      197.69         0.00   \n",
       "5       48067.99    43.61     6683.91     6556.47      127.44         0.00   \n",
       "6       73672.72    93.26     8318.86     8196.81      122.05         0.00   \n",
       "7      101815.36    80.00     6829.22     6266.85      562.37         0.00   \n",
       "8       87315.57    85.34    11388.36    11104.53      283.83         0.00   \n",
       "9       64757.44   113.00     8625.92     8061.47      564.45         0.00   \n",
       "10      75595.85   117.07     8205.66     7877.86      327.80         0.00   \n",
       "11      52677.92   105.32    10123.90     9866.27      257.63         0.00   \n",
       "12      49880.67   101.36     8756.75     8379.98      376.77         0.00   \n",
       "13      99409.21   154.84     6034.46     5888.87      145.59         0.00   \n",
       "14      59313.12   150.50     9267.36     8489.10      778.26         0.00   \n",
       "15      65696.86   142.00     9286.68     8665.19      621.49         0.00   \n",
       "16      90062.62   240.79     7990.10     7762.87      227.23         0.00   \n",
       "17      94362.67   335.43    10306.73    10218.93       87.80         0.00   \n",
       "18      67933.79   444.78    10880.36    10745.79      134.57         0.00   \n",
       "19      68666.01   394.90    10443.22    10297.68      145.54         0.00   \n",
       "20     100961.46   368.95     9225.89     9116.34      109.55         0.00   \n",
       "21      62035.06   741.08    11847.02    11768.52       78.50         0.00   \n",
       "22      91949.05   966.61    13192.69    13061.53      131.16         0.00   \n",
       "23      82049.40  2238.02    11287.48    11103.49      183.99         0.00   \n",
       "24      94693.52  4257.64    24431.90    24290.08      108.49        33.33   \n",
       "25      72600.55  5883.16    29898.96    29663.19      235.77         0.00   \n",
       "26      57545.79  4662.71    26662.08    26311.76      350.32         0.00   \n",
       "27      76688.55  5481.18    21875.65    21662.00      213.65         0.00   \n",
       "28      55400.94  4377.19    29002.59    28343.14      659.45         0.00   \n",
       "29      99220.82    90.32    22775.21    22314.99      460.22         0.00   \n",
       "...          ...      ...         ...         ...         ...          ...   \n",
       "18219  270798.27  1839.80   945638.02   768242.42   177144.00       251.60   \n",
       "18220  287724.61  1703.52   977084.84   774695.74   201878.69       510.41   \n",
       "18221  280080.34  1270.61   936859.49   796104.27   140652.84       102.38   \n",
       "18222  259172.13  1490.02   914409.26   710654.40   203526.59       228.27   \n",
       "18223  323669.83  1580.01  1005593.78   858772.69   146808.97        12.12   \n",
       "18224  296490.29  1289.07  1089861.24   915452.78   174381.57        26.89   \n",
       "18225   77861.39   117.56   166747.85    87108.00    79495.39       144.46   \n",
       "18226   47165.54   110.40   129353.55    73163.12    56020.24       170.19   \n",
       "18227   60383.57   276.42   176465.63   107174.93    69290.70         0.00   \n",
       "18228   71213.19    79.01   250090.37    85835.17   164087.33       167.87   \n",
       "18229   49139.34    85.58   218560.51    99989.62   118314.77       256.12   \n",
       "18230   38800.64   123.13   155725.83   120428.13    35257.73        39.97   \n",
       "18231   61713.53   243.00   188559.45    88497.05    99810.80       251.60   \n",
       "18232   55360.49   133.41   205409.91    70232.59   134666.91       510.41   \n",
       "18233   33051.14    93.52   129911.47    77822.23    51986.86       102.38   \n",
       "18234   33561.32   439.47   128267.76    76091.99    51947.50       228.27   \n",
       "18235   47435.14   433.52   126261.89    89115.78    37133.99        12.12   \n",
       "18236   62967.74   157.77   199330.12   103761.55    95544.39        24.18   \n",
       "18237    2171.66     0.00    10806.44    10569.80      236.64         0.00   \n",
       "18238    1499.55     0.00    12341.48    12114.81      226.67         0.00   \n",
       "18239    3194.25     8.93    16762.57    16510.32      252.25         0.00   \n",
       "18240    1905.57     0.00    13655.49    13401.93      253.56         0.00   \n",
       "18241    2482.65     0.00    13964.33    13698.27      266.06         0.00   \n",
       "18242    1928.36     0.00    13776.71    13553.53      223.18         0.00   \n",
       "18243    1368.32     0.00    12693.57    12437.35      256.22         0.00   \n",
       "18244    1529.20     0.00    13498.67    13066.82      431.85         0.00   \n",
       "18245    3431.50     0.00     9264.84     8940.04      324.80         0.00   \n",
       "18246    2452.79   727.94     9394.11     9351.80       42.31         0.00   \n",
       "18247    2981.04   727.01    10969.54    10919.54       50.00         0.00   \n",
       "18248    2356.13   224.53    12014.15    11988.14       26.01         0.00   \n",
       "\n",
       "               type  year            region  Conventional  \n",
       "0      conventional  2015            Albany          True  \n",
       "1      conventional  2015            Albany          True  \n",
       "2      conventional  2015            Albany          True  \n",
       "3      conventional  2015            Albany          True  \n",
       "4      conventional  2015            Albany          True  \n",
       "5      conventional  2015            Albany          True  \n",
       "6      conventional  2015            Albany          True  \n",
       "7      conventional  2015            Albany          True  \n",
       "8      conventional  2015            Albany          True  \n",
       "9      conventional  2015            Albany          True  \n",
       "10     conventional  2015            Albany          True  \n",
       "11     conventional  2015            Albany          True  \n",
       "12     conventional  2015            Albany          True  \n",
       "13     conventional  2015            Albany          True  \n",
       "14     conventional  2015            Albany          True  \n",
       "15     conventional  2015            Albany          True  \n",
       "16     conventional  2015            Albany          True  \n",
       "17     conventional  2015            Albany          True  \n",
       "18     conventional  2015            Albany          True  \n",
       "19     conventional  2015            Albany          True  \n",
       "20     conventional  2015            Albany          True  \n",
       "21     conventional  2015            Albany          True  \n",
       "22     conventional  2015            Albany          True  \n",
       "23     conventional  2015            Albany          True  \n",
       "24     conventional  2015            Albany          True  \n",
       "25     conventional  2015            Albany          True  \n",
       "26     conventional  2015            Albany          True  \n",
       "27     conventional  2015            Albany          True  \n",
       "28     conventional  2015            Albany          True  \n",
       "29     conventional  2015            Albany          True  \n",
       "...             ...   ...               ...           ...  \n",
       "18219       organic  2018           TotalUS         False  \n",
       "18220       organic  2018           TotalUS         False  \n",
       "18221       organic  2018           TotalUS         False  \n",
       "18222       organic  2018           TotalUS         False  \n",
       "18223       organic  2018           TotalUS         False  \n",
       "18224       organic  2018           TotalUS         False  \n",
       "18225       organic  2018              West         False  \n",
       "18226       organic  2018              West         False  \n",
       "18227       organic  2018              West         False  \n",
       "18228       organic  2018              West         False  \n",
       "18229       organic  2018              West         False  \n",
       "18230       organic  2018              West         False  \n",
       "18231       organic  2018              West         False  \n",
       "18232       organic  2018              West         False  \n",
       "18233       organic  2018              West         False  \n",
       "18234       organic  2018              West         False  \n",
       "18235       organic  2018              West         False  \n",
       "18236       organic  2018              West         False  \n",
       "18237       organic  2018  WestTexNewMexico         False  \n",
       "18238       organic  2018  WestTexNewMexico         False  \n",
       "18239       organic  2018  WestTexNewMexico         False  \n",
       "18240       organic  2018  WestTexNewMexico         False  \n",
       "18241       organic  2018  WestTexNewMexico         False  \n",
       "18242       organic  2018  WestTexNewMexico         False  \n",
       "18243       organic  2018  WestTexNewMexico         False  \n",
       "18244       organic  2018  WestTexNewMexico         False  \n",
       "18245       organic  2018  WestTexNewMexico         False  \n",
       "18246       organic  2018  WestTexNewMexico         False  \n",
       "18247       organic  2018  WestTexNewMexico         False  \n",
       "18248       organic  2018  WestTexNewMexico         False  \n",
       "\n",
       "[18249 rows x 15 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado[\"Conventional\"] = True\n",
    "avocado[\"Conventional\"].loc[avocado[\"type\"] == \"organic\"] = False\n",
    "avocado"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Grouping \n",
    "What if we wanted to find how many entries we have that are conventional and organic? We can do this in multiple ways. First we can do it by using the **df.groupby()** function and then calling **.size()**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "conventional    9126\n",
       "organic         9123\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_count = avocado.groupby(\"type\").size()\n",
    "type_count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we can also use the **SERIES.value_counts()** function. First we have to indicate what column we are trying to count."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "conventional    9126\n",
       "organic         9123\n",
       "Name: type, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type_count_alt = avocado[\"type\"].value_counts()\n",
    "type_count_alt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also order series by using the **sort_values()** function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2017    5722\n",
       "2016    5616\n",
       "2015    5615\n",
       "2018    1296\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "region = avocado[\"year\"].value_counts()\n",
    "region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2018    1296\n",
       "2015    5615\n",
       "2016    5616\n",
       "2017    5722\n",
       "Name: year, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "region.sort_values(ascending = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregate Function\n",
    "\n",
    "Let's explore what the average count of each type of avocados are in each respective year. Agg aggregates data by a certain function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>304443</td>\n",
       "      <td>313633</td>\n",
       "      <td>25426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>271567</td>\n",
       "      <td>297850</td>\n",
       "      <td>28468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>288716</td>\n",
       "      <td>269964</td>\n",
       "      <td>15941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>355323</td>\n",
       "      <td>314628</td>\n",
       "      <td>17694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        4046    4225   4770\n",
       "year                       \n",
       "2015  304443  313633  25426\n",
       "2016  271567  297850  28468\n",
       "2017  288716  269964  15941\n",
       "2018  355323  314628  17694"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado[[\"year\", \"4046\", \"4225\", \"4770\"]].groupby(\"year\").agg(np.mean).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas Data Types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. object: data type for strings (sequence of characters)\n",
    "2. int64: integer numbers\n",
    "3. float64: floating point numbers\n",
    "4. bool: true/false values\n",
    "5. datetime: date and time values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.info of        Unnamed: 0        Date  AveragePrice  Total Volume       4046  \\\n",
       "0               0  2015-12-27          1.33      64236.62    1036.74   \n",
       "1               1  2015-12-20          1.35      54876.98     674.28   \n",
       "2               2  2015-12-13          0.93     118220.22     794.70   \n",
       "3               3  2015-12-06          1.08      78992.15    1132.00   \n",
       "4               4  2015-11-29          1.28      51039.60     941.48   \n",
       "5               5  2015-11-22          1.26      55979.78    1184.27   \n",
       "6               6  2015-11-15          0.99      83453.76    1368.92   \n",
       "7               7  2015-11-08          0.98     109428.33     703.75   \n",
       "8               8  2015-11-01          1.02      99811.42    1022.15   \n",
       "9               9  2015-10-25          1.07      74338.76     842.40   \n",
       "10             10  2015-10-18          1.12      84843.44     924.86   \n",
       "11             11  2015-10-11          1.28      64489.17    1582.03   \n",
       "12             12  2015-10-04          1.31      61007.10    2268.32   \n",
       "13             13  2015-09-27          0.99     106803.39    1204.88   \n",
       "14             14  2015-09-20          1.33      69759.01    1028.03   \n",
       "15             15  2015-09-13          1.28      76111.27     985.73   \n",
       "16             16  2015-09-06          1.11      99172.96     879.45   \n",
       "17             17  2015-08-30          1.07     105693.84     689.01   \n",
       "18             18  2015-08-23          1.34      79992.09     733.16   \n",
       "19             19  2015-08-16          1.33      80043.78     539.65   \n",
       "20             20  2015-08-09          1.12     111140.93     584.63   \n",
       "21             21  2015-08-02          1.45      75133.10     509.94   \n",
       "22             22  2015-07-26          1.11     106757.10     648.75   \n",
       "23             23  2015-07-19          1.26      96617.00    1042.10   \n",
       "24             24  2015-07-12          1.05     124055.31     672.25   \n",
       "25             25  2015-07-05          1.35     109252.12     869.45   \n",
       "26             26  2015-06-28          1.37      89534.81     664.23   \n",
       "27             27  2015-06-21          1.27     104849.39     804.01   \n",
       "28             28  2015-06-14          1.32      89631.30     850.58   \n",
       "29             29  2015-06-07          1.07     122743.06     656.71   \n",
       "...           ...         ...           ...           ...        ...   \n",
       "18219           6  2018-02-11          1.56    1317000.47   98465.26   \n",
       "18220           7  2018-02-04          1.53    1384683.41  117922.52   \n",
       "18221           8  2018-01-28          1.61    1336979.09  118616.17   \n",
       "18222           9  2018-01-21          1.63    1283987.65  108705.28   \n",
       "18223          10  2018-01-14          1.59    1476651.08  145680.62   \n",
       "18224          11  2018-01-07          1.51    1517332.70  129541.43   \n",
       "18225           0  2018-03-25          1.60     271723.08   26996.28   \n",
       "18226           1  2018-03-18          1.73     210067.47   33437.98   \n",
       "18227           2  2018-03-11          1.63     264691.87   27566.25   \n",
       "18228           3  2018-03-04          1.46     347373.17   25990.60   \n",
       "18229           4  2018-02-25          1.49     301985.61   34200.18   \n",
       "18230           5  2018-02-18          1.64     224798.60   30149.00   \n",
       "18231           6  2018-02-11          1.47     275248.53   24732.55   \n",
       "18232           7  2018-02-04          1.41     283378.47   22474.66   \n",
       "18233           8  2018-01-28          1.80     185974.53   22918.40   \n",
       "18234           9  2018-01-21          1.83     189317.99   27049.44   \n",
       "18235          10  2018-01-14          1.82     207999.67   33869.12   \n",
       "18236          11  2018-01-07          1.48     297190.60   34734.97   \n",
       "18237           0  2018-03-25          1.62      15303.40    2325.30   \n",
       "18238           1  2018-03-18          1.56      15896.38    2055.35   \n",
       "18239           2  2018-03-11          1.56      22128.42    2162.67   \n",
       "18240           3  2018-03-04          1.54      17393.30    1832.24   \n",
       "18241           4  2018-02-25          1.57      18421.24    1974.26   \n",
       "18242           5  2018-02-18          1.56      17597.12    1892.05   \n",
       "18243           6  2018-02-11          1.57      15986.17    1924.28   \n",
       "18244           7  2018-02-04          1.63      17074.83    2046.96   \n",
       "18245           8  2018-01-28          1.71      13888.04    1191.70   \n",
       "18246           9  2018-01-21          1.87      13766.76    1191.92   \n",
       "18247          10  2018-01-14          1.93      16205.22    1527.63   \n",
       "18248          11  2018-01-07          1.62      17489.58    2894.77   \n",
       "\n",
       "            4225     4770  Total Bags  Small Bags  Large Bags  XLarge Bags  \\\n",
       "0       54454.85    48.16     8696.87     8603.62       93.25         0.00   \n",
       "1       44638.81    58.33     9505.56     9408.07       97.49         0.00   \n",
       "2      109149.67   130.50     8145.35     8042.21      103.14         0.00   \n",
       "3       71976.41    72.58     5811.16     5677.40      133.76         0.00   \n",
       "4       43838.39    75.78     6183.95     5986.26      197.69         0.00   \n",
       "5       48067.99    43.61     6683.91     6556.47      127.44         0.00   \n",
       "6       73672.72    93.26     8318.86     8196.81      122.05         0.00   \n",
       "7      101815.36    80.00     6829.22     6266.85      562.37         0.00   \n",
       "8       87315.57    85.34    11388.36    11104.53      283.83         0.00   \n",
       "9       64757.44   113.00     8625.92     8061.47      564.45         0.00   \n",
       "10      75595.85   117.07     8205.66     7877.86      327.80         0.00   \n",
       "11      52677.92   105.32    10123.90     9866.27      257.63         0.00   \n",
       "12      49880.67   101.36     8756.75     8379.98      376.77         0.00   \n",
       "13      99409.21   154.84     6034.46     5888.87      145.59         0.00   \n",
       "14      59313.12   150.50     9267.36     8489.10      778.26         0.00   \n",
       "15      65696.86   142.00     9286.68     8665.19      621.49         0.00   \n",
       "16      90062.62   240.79     7990.10     7762.87      227.23         0.00   \n",
       "17      94362.67   335.43    10306.73    10218.93       87.80         0.00   \n",
       "18      67933.79   444.78    10880.36    10745.79      134.57         0.00   \n",
       "19      68666.01   394.90    10443.22    10297.68      145.54         0.00   \n",
       "20     100961.46   368.95     9225.89     9116.34      109.55         0.00   \n",
       "21      62035.06   741.08    11847.02    11768.52       78.50         0.00   \n",
       "22      91949.05   966.61    13192.69    13061.53      131.16         0.00   \n",
       "23      82049.40  2238.02    11287.48    11103.49      183.99         0.00   \n",
       "24      94693.52  4257.64    24431.90    24290.08      108.49        33.33   \n",
       "25      72600.55  5883.16    29898.96    29663.19      235.77         0.00   \n",
       "26      57545.79  4662.71    26662.08    26311.76      350.32         0.00   \n",
       "27      76688.55  5481.18    21875.65    21662.00      213.65         0.00   \n",
       "28      55400.94  4377.19    29002.59    28343.14      659.45         0.00   \n",
       "29      99220.82    90.32    22775.21    22314.99      460.22         0.00   \n",
       "...          ...      ...         ...         ...         ...          ...   \n",
       "18219  270798.27  1839.80   945638.02   768242.42   177144.00       251.60   \n",
       "18220  287724.61  1703.52   977084.84   774695.74   201878.69       510.41   \n",
       "18221  280080.34  1270.61   936859.49   796104.27   140652.84       102.38   \n",
       "18222  259172.13  1490.02   914409.26   710654.40   203526.59       228.27   \n",
       "18223  323669.83  1580.01  1005593.78   858772.69   146808.97        12.12   \n",
       "18224  296490.29  1289.07  1089861.24   915452.78   174381.57        26.89   \n",
       "18225   77861.39   117.56   166747.85    87108.00    79495.39       144.46   \n",
       "18226   47165.54   110.40   129353.55    73163.12    56020.24       170.19   \n",
       "18227   60383.57   276.42   176465.63   107174.93    69290.70         0.00   \n",
       "18228   71213.19    79.01   250090.37    85835.17   164087.33       167.87   \n",
       "18229   49139.34    85.58   218560.51    99989.62   118314.77       256.12   \n",
       "18230   38800.64   123.13   155725.83   120428.13    35257.73        39.97   \n",
       "18231   61713.53   243.00   188559.45    88497.05    99810.80       251.60   \n",
       "18232   55360.49   133.41   205409.91    70232.59   134666.91       510.41   \n",
       "18233   33051.14    93.52   129911.47    77822.23    51986.86       102.38   \n",
       "18234   33561.32   439.47   128267.76    76091.99    51947.50       228.27   \n",
       "18235   47435.14   433.52   126261.89    89115.78    37133.99        12.12   \n",
       "18236   62967.74   157.77   199330.12   103761.55    95544.39        24.18   \n",
       "18237    2171.66     0.00    10806.44    10569.80      236.64         0.00   \n",
       "18238    1499.55     0.00    12341.48    12114.81      226.67         0.00   \n",
       "18239    3194.25     8.93    16762.57    16510.32      252.25         0.00   \n",
       "18240    1905.57     0.00    13655.49    13401.93      253.56         0.00   \n",
       "18241    2482.65     0.00    13964.33    13698.27      266.06         0.00   \n",
       "18242    1928.36     0.00    13776.71    13553.53      223.18         0.00   \n",
       "18243    1368.32     0.00    12693.57    12437.35      256.22         0.00   \n",
       "18244    1529.20     0.00    13498.67    13066.82      431.85         0.00   \n",
       "18245    3431.50     0.00     9264.84     8940.04      324.80         0.00   \n",
       "18246    2452.79   727.94     9394.11     9351.80       42.31         0.00   \n",
       "18247    2981.04   727.01    10969.54    10919.54       50.00         0.00   \n",
       "18248    2356.13   224.53    12014.15    11988.14       26.01         0.00   \n",
       "\n",
       "               type  year            region  Conventional  \n",
       "0      conventional  2015            Albany          True  \n",
       "1      conventional  2015            Albany          True  \n",
       "2      conventional  2015            Albany          True  \n",
       "3      conventional  2015            Albany          True  \n",
       "4      conventional  2015            Albany          True  \n",
       "5      conventional  2015            Albany          True  \n",
       "6      conventional  2015            Albany          True  \n",
       "7      conventional  2015            Albany          True  \n",
       "8      conventional  2015            Albany          True  \n",
       "9      conventional  2015            Albany          True  \n",
       "10     conventional  2015            Albany          True  \n",
       "11     conventional  2015            Albany          True  \n",
       "12     conventional  2015            Albany          True  \n",
       "13     conventional  2015            Albany          True  \n",
       "14     conventional  2015            Albany          True  \n",
       "15     conventional  2015            Albany          True  \n",
       "16     conventional  2015            Albany          True  \n",
       "17     conventional  2015            Albany          True  \n",
       "18     conventional  2015            Albany          True  \n",
       "19     conventional  2015            Albany          True  \n",
       "20     conventional  2015            Albany          True  \n",
       "21     conventional  2015            Albany          True  \n",
       "22     conventional  2015            Albany          True  \n",
       "23     conventional  2015            Albany          True  \n",
       "24     conventional  2015            Albany          True  \n",
       "25     conventional  2015            Albany          True  \n",
       "26     conventional  2015            Albany          True  \n",
       "27     conventional  2015            Albany          True  \n",
       "28     conventional  2015            Albany          True  \n",
       "29     conventional  2015            Albany          True  \n",
       "...             ...   ...               ...           ...  \n",
       "18219       organic  2018           TotalUS         False  \n",
       "18220       organic  2018           TotalUS         False  \n",
       "18221       organic  2018           TotalUS         False  \n",
       "18222       organic  2018           TotalUS         False  \n",
       "18223       organic  2018           TotalUS         False  \n",
       "18224       organic  2018           TotalUS         False  \n",
       "18225       organic  2018              West         False  \n",
       "18226       organic  2018              West         False  \n",
       "18227       organic  2018              West         False  \n",
       "18228       organic  2018              West         False  \n",
       "18229       organic  2018              West         False  \n",
       "18230       organic  2018              West         False  \n",
       "18231       organic  2018              West         False  \n",
       "18232       organic  2018              West         False  \n",
       "18233       organic  2018              West         False  \n",
       "18234       organic  2018              West         False  \n",
       "18235       organic  2018              West         False  \n",
       "18236       organic  2018              West         False  \n",
       "18237       organic  2018  WestTexNewMexico         False  \n",
       "18238       organic  2018  WestTexNewMexico         False  \n",
       "18239       organic  2018  WestTexNewMexico         False  \n",
       "18240       organic  2018  WestTexNewMexico         False  \n",
       "18241       organic  2018  WestTexNewMexico         False  \n",
       "18242       organic  2018  WestTexNewMexico         False  \n",
       "18243       organic  2018  WestTexNewMexico         False  \n",
       "18244       organic  2018  WestTexNewMexico         False  \n",
       "18245       organic  2018  WestTexNewMexico         False  \n",
       "18246       organic  2018  WestTexNewMexico         False  \n",
       "18247       organic  2018  WestTexNewMexico         False  \n",
       "18248       organic  2018  WestTexNewMexico         False  \n",
       "\n",
       "[18249 rows x 15 columns]>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado.info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Changing Data Types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's say for the sake of simpler computations we want to remove the decimals from our \"Total Volume\" column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>type</th>\n",
       "      <th>year</th>\n",
       "      <th>region</th>\n",
       "      <th>Conventional</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>1.33</td>\n",
       "      <td>64236</td>\n",
       "      <td>1036.74</td>\n",
       "      <td>54454.85</td>\n",
       "      <td>48.16</td>\n",
       "      <td>8696.87</td>\n",
       "      <td>8603.62</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-12-20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>54876</td>\n",
       "      <td>674.28</td>\n",
       "      <td>44638.81</td>\n",
       "      <td>58.33</td>\n",
       "      <td>9505.56</td>\n",
       "      <td>9408.07</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-12-13</td>\n",
       "      <td>0.93</td>\n",
       "      <td>118220</td>\n",
       "      <td>794.70</td>\n",
       "      <td>109149.67</td>\n",
       "      <td>130.50</td>\n",
       "      <td>8145.35</td>\n",
       "      <td>8042.21</td>\n",
       "      <td>103.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-12-06</td>\n",
       "      <td>1.08</td>\n",
       "      <td>78992</td>\n",
       "      <td>1132.00</td>\n",
       "      <td>71976.41</td>\n",
       "      <td>72.58</td>\n",
       "      <td>5811.16</td>\n",
       "      <td>5677.40</td>\n",
       "      <td>133.76</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-11-29</td>\n",
       "      <td>1.28</td>\n",
       "      <td>51039</td>\n",
       "      <td>941.48</td>\n",
       "      <td>43838.39</td>\n",
       "      <td>75.78</td>\n",
       "      <td>6183.95</td>\n",
       "      <td>5986.26</td>\n",
       "      <td>197.69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>conventional</td>\n",
       "      <td>2015</td>\n",
       "      <td>Albany</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0        Date  AveragePrice  Total Volume     4046       4225  \\\n",
       "0           0  2015-12-27          1.33         64236  1036.74   54454.85   \n",
       "1           1  2015-12-20          1.35         54876   674.28   44638.81   \n",
       "2           2  2015-12-13          0.93        118220   794.70  109149.67   \n",
       "3           3  2015-12-06          1.08         78992  1132.00   71976.41   \n",
       "4           4  2015-11-29          1.28         51039   941.48   43838.39   \n",
       "\n",
       "     4770  Total Bags  Small Bags  Large Bags  XLarge Bags          type  \\\n",
       "0   48.16     8696.87     8603.62       93.25          0.0  conventional   \n",
       "1   58.33     9505.56     9408.07       97.49          0.0  conventional   \n",
       "2  130.50     8145.35     8042.21      103.14          0.0  conventional   \n",
       "3   72.58     5811.16     5677.40      133.76          0.0  conventional   \n",
       "4   75.78     6183.95     5986.26      197.69          0.0  conventional   \n",
       "\n",
       "   year  region  Conventional  \n",
       "0  2015  Albany          True  \n",
       "1  2015  Albany          True  \n",
       "2  2015  Albany          True  \n",
       "3  2015  Albany          True  \n",
       "4  2015  Albany          True  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado[\"Total Volume\"] = avocado[\"Total Volume\"].astype(int)\n",
    "avocado.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the **.astype()** function to change values to a bunch of differet data types."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Useful Pandas Functions\n",
    "One of the most helpful functions of pandas is the **df.describe()** function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>AveragePrice</th>\n",
       "      <th>Total Volume</th>\n",
       "      <th>4046</th>\n",
       "      <th>4225</th>\n",
       "      <th>4770</th>\n",
       "      <th>Total Bags</th>\n",
       "      <th>Small Bags</th>\n",
       "      <th>Large Bags</th>\n",
       "      <th>XLarge Bags</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>18249.000000</td>\n",
       "      <td>18249.000000</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>1.824900e+04</td>\n",
       "      <td>18249.000000</td>\n",
       "      <td>18249.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>24.232232</td>\n",
       "      <td>1.405978</td>\n",
       "      <td>8.506440e+05</td>\n",
       "      <td>2.930084e+05</td>\n",
       "      <td>2.951546e+05</td>\n",
       "      <td>2.283974e+04</td>\n",
       "      <td>2.396392e+05</td>\n",
       "      <td>1.821947e+05</td>\n",
       "      <td>5.433809e+04</td>\n",
       "      <td>3106.426507</td>\n",
       "      <td>2016.147899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15.481045</td>\n",
       "      <td>0.402677</td>\n",
       "      <td>3.453545e+06</td>\n",
       "      <td>1.264989e+06</td>\n",
       "      <td>1.204120e+06</td>\n",
       "      <td>1.074641e+05</td>\n",
       "      <td>9.862424e+05</td>\n",
       "      <td>7.461785e+05</td>\n",
       "      <td>2.439660e+05</td>\n",
       "      <td>17692.894652</td>\n",
       "      <td>0.939938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.440000</td>\n",
       "      <td>8.456000e+01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2015.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>1.083858e+04</td>\n",
       "      <td>8.540700e+02</td>\n",
       "      <td>3.008780e+03</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.088640e+03</td>\n",
       "      <td>2.849420e+03</td>\n",
       "      <td>1.274700e+02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2015.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>24.000000</td>\n",
       "      <td>1.370000</td>\n",
       "      <td>1.073768e+05</td>\n",
       "      <td>8.645300e+03</td>\n",
       "      <td>2.906102e+04</td>\n",
       "      <td>1.849900e+02</td>\n",
       "      <td>3.974383e+04</td>\n",
       "      <td>2.636282e+04</td>\n",
       "      <td>2.647710e+03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2016.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.660000</td>\n",
       "      <td>4.329623e+05</td>\n",
       "      <td>1.110202e+05</td>\n",
       "      <td>1.502069e+05</td>\n",
       "      <td>6.243420e+03</td>\n",
       "      <td>1.107834e+05</td>\n",
       "      <td>8.333767e+04</td>\n",
       "      <td>2.202925e+04</td>\n",
       "      <td>132.500000</td>\n",
       "      <td>2017.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>3.250000</td>\n",
       "      <td>6.250565e+07</td>\n",
       "      <td>2.274362e+07</td>\n",
       "      <td>2.047057e+07</td>\n",
       "      <td>2.546439e+06</td>\n",
       "      <td>1.937313e+07</td>\n",
       "      <td>1.338459e+07</td>\n",
       "      <td>5.719097e+06</td>\n",
       "      <td>551693.650000</td>\n",
       "      <td>2018.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Unnamed: 0  AveragePrice  Total Volume          4046          4225  \\\n",
       "count  18249.000000  18249.000000  1.824900e+04  1.824900e+04  1.824900e+04   \n",
       "mean      24.232232      1.405978  8.506440e+05  2.930084e+05  2.951546e+05   \n",
       "std       15.481045      0.402677  3.453545e+06  1.264989e+06  1.204120e+06   \n",
       "min        0.000000      0.440000  8.456000e+01  0.000000e+00  0.000000e+00   \n",
       "25%       10.000000      1.100000  1.083858e+04  8.540700e+02  3.008780e+03   \n",
       "50%       24.000000      1.370000  1.073768e+05  8.645300e+03  2.906102e+04   \n",
       "75%       38.000000      1.660000  4.329623e+05  1.110202e+05  1.502069e+05   \n",
       "max       52.000000      3.250000  6.250565e+07  2.274362e+07  2.047057e+07   \n",
       "\n",
       "               4770    Total Bags    Small Bags    Large Bags    XLarge Bags  \\\n",
       "count  1.824900e+04  1.824900e+04  1.824900e+04  1.824900e+04   18249.000000   \n",
       "mean   2.283974e+04  2.396392e+05  1.821947e+05  5.433809e+04    3106.426507   \n",
       "std    1.074641e+05  9.862424e+05  7.461785e+05  2.439660e+05   17692.894652   \n",
       "min    0.000000e+00  0.000000e+00  0.000000e+00  0.000000e+00       0.000000   \n",
       "25%    0.000000e+00  5.088640e+03  2.849420e+03  1.274700e+02       0.000000   \n",
       "50%    1.849900e+02  3.974383e+04  2.636282e+04  2.647710e+03       0.000000   \n",
       "75%    6.243420e+03  1.107834e+05  8.333767e+04  2.202925e+04     132.500000   \n",
       "max    2.546439e+06  1.937313e+07  1.338459e+07  5.719097e+06  551693.650000   \n",
       "\n",
       "               year  \n",
       "count  18249.000000  \n",
       "mean    2016.147899  \n",
       "std        0.939938  \n",
       "min     2015.000000  \n",
       "25%     2015.000000  \n",
       "50%     2016.000000  \n",
       "75%     2017.000000  \n",
       "max     2018.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the dataframe shows a bunch of useful metrics about our table that we didn't have to calculate ourselves!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This shows all of our columns and what type of data is in each column! This is useful if you saw a number in your data, but you weren't sure if it was an int or a string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0        int64\n",
       "Date             object\n",
       "AveragePrice    float64\n",
       "Total Volume      int64\n",
       "4046            float64\n",
       "4225            float64\n",
       "4770            float64\n",
       "Total Bags      float64\n",
       "Small Bags      float64\n",
       "Large Bags      float64\n",
       "XLarge Bags     float64\n",
       "type             object\n",
       "year              int64\n",
       "region           object\n",
       "Conventional       bool\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avocado.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pivot Tables\n",
    "\n",
    "What if we want to reshape the table? Let's use the pivot table function to expand, isolate, and modify our table in a condensed matter. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Classes</th>\n",
       "      <th>Professors</th>\n",
       "      <th>Average Grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CS61A</td>\n",
       "      <td>Denero</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Data 8</td>\n",
       "      <td>Adhikari</td>\n",
       "      <td>A-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CS61B</td>\n",
       "      <td>Hilfinger</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Classes Professors Average Grade\n",
       "0   CS61A     Denero            B+\n",
       "1  Data 8   Adhikari            A-\n",
       "2   CS61B  Hilfinger            B+"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example \n",
    "  \n",
    "classes = pd.DataFrame({'Classes': ['CS61A', 'Data 8', 'CS61B'], \n",
    "      'Professors': ['Denero', 'Adhikari', 'Hilfinger'], \n",
    "      'Average Grade': [\"B+\", \"A-\", \"B+\"]}) \n",
    "classes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Average Grade</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professors</th>\n",
       "      <th>Adhikari</th>\n",
       "      <th>Denero</th>\n",
       "      <th>Hilfinger</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Classes</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CS61A</th>\n",
       "      <td>NaN</td>\n",
       "      <td>B+</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CS61B</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data 8</th>\n",
       "      <td>A-</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Average Grade                 \n",
       "Professors      Adhikari Denero Hilfinger\n",
       "Classes                                  \n",
       "CS61A                NaN     B+       NaN\n",
       "CS61B                NaN    NaN        B+\n",
       "Data 8                A-    NaN       NaN"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes.pivot(index ='Classes', columns ='Professors', values = ['Average Grade']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Average Grade</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professors</th>\n",
       "      <th>Adhikari</th>\n",
       "      <th>Denero</th>\n",
       "      <th>Hilfinger</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>B+</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A-</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Average Grade                 \n",
       "Professors      Adhikari Denero Hilfinger\n",
       "0                    NaN     B+       NaN\n",
       "1                     A-    NaN       NaN\n",
       "2                    NaN    NaN        B+"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes.pivot(columns ='Professors', values = ['Average Grade']) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try this with our avocado data! I am interested in seeing a table with the type of Haas Avocados as columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">AveragePrice</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Total Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>type</th>\n",
       "      <th>conventional</th>\n",
       "      <th>organic</th>\n",
       "      <th>conventional</th>\n",
       "      <th>organic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64236.62</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54876.98</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118220.22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78992.15</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51039.60</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55979.78</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83453.76</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109428.33</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99811.42</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74338.76</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>84843.44</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>64489.17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61007.10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106803.39</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>69759.01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76111.27</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>99172.96</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105693.84</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79992.09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80043.78</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111140.93</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75133.10</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106757.10</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96617.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>124055.31</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109252.12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1.37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89534.81</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104849.39</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1.32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89631.30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1.07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>122743.06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18219</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1317000.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18220</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384683.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18221</th>\n",
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       "      <td>1.61</td>\n",
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       "    <tr>\n",
       "      <th>18222</th>\n",
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       "      <td>1.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1283987.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18223</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1476651.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18224</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1517332.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18225</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>271723.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18226</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>210067.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18227</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>264691.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18228</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>347373.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18229</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>301985.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18230</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>224798.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18231</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>275248.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18232</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>283378.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18233</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>185974.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18234</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>189317.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18235</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.82</td>\n",
       "      <td>NaN</td>\n",
       "      <td>207999.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18236</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>297190.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18237</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15303.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18238</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15896.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18239</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22128.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18240</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17393.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18241</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18421.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18242</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17597.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18243</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15986.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18244</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17074.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18245</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13888.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18246</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13766.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18247</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16205.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18248</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17489.58</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18249 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      AveragePrice         Total Volume            \n",
       "type  conventional organic conventional     organic\n",
       "0             1.33     NaN     64236.62         NaN\n",
       "1             1.35     NaN     54876.98         NaN\n",
       "2             0.93     NaN    118220.22         NaN\n",
       "3             1.08     NaN     78992.15         NaN\n",
       "4             1.28     NaN     51039.60         NaN\n",
       "5             1.26     NaN     55979.78         NaN\n",
       "6             0.99     NaN     83453.76         NaN\n",
       "7             0.98     NaN    109428.33         NaN\n",
       "8             1.02     NaN     99811.42         NaN\n",
       "9             1.07     NaN     74338.76         NaN\n",
       "10            1.12     NaN     84843.44         NaN\n",
       "11            1.28     NaN     64489.17         NaN\n",
       "12            1.31     NaN     61007.10         NaN\n",
       "13            0.99     NaN    106803.39         NaN\n",
       "14            1.33     NaN     69759.01         NaN\n",
       "15            1.28     NaN     76111.27         NaN\n",
       "16            1.11     NaN     99172.96         NaN\n",
       "17            1.07     NaN    105693.84         NaN\n",
       "18            1.34     NaN     79992.09         NaN\n",
       "19            1.33     NaN     80043.78         NaN\n",
       "20            1.12     NaN    111140.93         NaN\n",
       "21            1.45     NaN     75133.10         NaN\n",
       "22            1.11     NaN    106757.10         NaN\n",
       "23            1.26     NaN     96617.00         NaN\n",
       "24            1.05     NaN    124055.31         NaN\n",
       "25            1.35     NaN    109252.12         NaN\n",
       "26            1.37     NaN     89534.81         NaN\n",
       "27            1.27     NaN    104849.39         NaN\n",
       "28            1.32     NaN     89631.30         NaN\n",
       "29            1.07     NaN    122743.06         NaN\n",
       "...            ...     ...          ...         ...\n",
       "18219          NaN    1.56          NaN  1317000.47\n",
       "18220          NaN    1.53          NaN  1384683.41\n",
       "18221          NaN    1.61          NaN  1336979.09\n",
       "18222          NaN    1.63          NaN  1283987.65\n",
       "18223          NaN    1.59          NaN  1476651.08\n",
       "18224          NaN    1.51          NaN  1517332.70\n",
       "18225          NaN    1.60          NaN   271723.08\n",
       "18226          NaN    1.73          NaN   210067.47\n",
       "18227          NaN    1.63          NaN   264691.87\n",
       "18228          NaN    1.46          NaN   347373.17\n",
       "18229          NaN    1.49          NaN   301985.61\n",
       "18230          NaN    1.64          NaN   224798.60\n",
       "18231          NaN    1.47          NaN   275248.53\n",
       "18232          NaN    1.41          NaN   283378.47\n",
       "18233          NaN    1.80          NaN   185974.53\n",
       "18234          NaN    1.83          NaN   189317.99\n",
       "18235          NaN    1.82          NaN   207999.67\n",
       "18236          NaN    1.48          NaN   297190.60\n",
       "18237          NaN    1.62          NaN    15303.40\n",
       "18238          NaN    1.56          NaN    15896.38\n",
       "18239          NaN    1.56          NaN    22128.42\n",
       "18240          NaN    1.54          NaN    17393.30\n",
       "18241          NaN    1.57          NaN    18421.24\n",
       "18242          NaN    1.56          NaN    17597.12\n",
       "18243          NaN    1.57          NaN    15986.17\n",
       "18244          NaN    1.63          NaN    17074.83\n",
       "18245          NaN    1.71          NaN    13888.04\n",
       "18246          NaN    1.87          NaN    13766.76\n",
       "18247          NaN    1.93          NaN    16205.22\n",
       "18248          NaN    1.62          NaN    17489.58\n",
       "\n",
       "[18249 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivotedTable = avocado.pivot(columns = \"type\", values = [\"AveragePrice\", \"Total Volume\"])\n",
    "pivotedTable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Team Formation \n",
    "\n",
    "Now we will spend some time talking about some project ideas for you all to explore!\n",
    "\n",
    "Before we do that, let's talk about forming project teams! We talked about how important it is for you all to pick teammates that are all taking the same classes with you. However, it's almost important for members who share the same interest as you. If you all have the same interests, you will have an easier time picking a dataset to work on."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Project Ideas\n",
    "\n",
    "**Hypothesis Testing:** Is there a correlation between a day of the week and number of police phone calls? \n",
    "\n",
    "**Prediction:** Does the price of an iPhone app affect the rating? Will an iPhone app that cost more have a higher rating?\n",
    "                \n",
    "Predicting who's gonna be drafted in the NBA based off of player statistics.\n",
    "\n",
    "**Machine Learning:** Given someone's top 10 movie choices, reccommend a new movie.\n",
    "\n",
    "There are so many more projects that you can come up with! In the following lectures, we will give you the tools to complete a myraid of different data science projects. Some of future topics include visualization, machine learning, and Exploratory Data Analysis!"
   ]
  }
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