Stage_A.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['record_id', 'utility_id_ferc1', 'report_year', 'plant_name_ferc1',\n",
      "       'fuel_type_code_pudl', 'fuel_unit', 'fuel_qty_burned',\n",
      "       'fuel_mmbtu_per_unit', 'fuel_cost_per_unit_burned',\n",
      "       'fuel_cost_per_unit_delivered', 'fuel_cost_per_mmbtu'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "#reading data\n",
    "dataset = pd.read_csv(\"https://raw.githubusercontent.com/WalePhenomenon/climate_change/master/fuel_ferc1.csv\")\n",
    "\n",
    "data = pd.DataFrame(dataset) #converting to pandas DataFrame\n",
    "\n",
    "print(data.columns) #Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 1, 2]\n",
      "[1, 2, 1, 2, [1, 2]]\n"
     ]
    }
   ],
   "source": [
    "A = [1,2]\n",
    "B = [1,2]\n",
    "A.extend(B)\n",
    "print(A)\n",
    "A.append(B)\n",
    "print(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0.],\n",
       "       [0., 1., 0.],\n",
       "       [0., 0., 1.]])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.identity(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>utility_id_ferc1</th>\n",
       "      <th>report_year</th>\n",
       "      <th>fuel_qty_burned</th>\n",
       "      <th>fuel_mmbtu_per_unit</th>\n",
       "      <th>fuel_cost_per_unit_burned</th>\n",
       "      <th>fuel_cost_per_unit_delivered</th>\n",
       "      <th>fuel_cost_per_mmbtu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>29523.000000</td>\n",
       "      <td>29523.000000</td>\n",
       "      <td>2.952300e+04</td>\n",
       "      <td>29523.000000</td>\n",
       "      <td>29523.000000</td>\n",
       "      <td>2.952300e+04</td>\n",
       "      <td>29523.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>118.601836</td>\n",
       "      <td>2005.806050</td>\n",
       "      <td>2.622119e+06</td>\n",
       "      <td>8.492111</td>\n",
       "      <td>208.649031</td>\n",
       "      <td>9.175704e+02</td>\n",
       "      <td>19.304354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>74.178353</td>\n",
       "      <td>7.025483</td>\n",
       "      <td>9.118004e+06</td>\n",
       "      <td>10.600220</td>\n",
       "      <td>2854.490090</td>\n",
       "      <td>6.877593e+04</td>\n",
       "      <td>2091.540939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1994.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>-276.080000</td>\n",
       "      <td>-8.749370e+02</td>\n",
       "      <td>-41.501000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>1.381700e+04</td>\n",
       "      <td>1.024000</td>\n",
       "      <td>5.207000</td>\n",
       "      <td>3.778500e+00</td>\n",
       "      <td>1.940000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>122.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "      <td>2.533220e+05</td>\n",
       "      <td>5.762694</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>1.737100e+01</td>\n",
       "      <td>4.127000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>176.000000</td>\n",
       "      <td>2012.000000</td>\n",
       "      <td>1.424034e+06</td>\n",
       "      <td>17.006000</td>\n",
       "      <td>47.113000</td>\n",
       "      <td>4.213700e+01</td>\n",
       "      <td>7.745000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>514.000000</td>\n",
       "      <td>2018.000000</td>\n",
       "      <td>5.558942e+08</td>\n",
       "      <td>341.260000</td>\n",
       "      <td>139358.000000</td>\n",
       "      <td>7.964521e+06</td>\n",
       "      <td>359278.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       utility_id_ferc1   report_year  fuel_qty_burned  fuel_mmbtu_per_unit  \\\n",
       "count      29523.000000  29523.000000     2.952300e+04         29523.000000   \n",
       "mean         118.601836   2005.806050     2.622119e+06             8.492111   \n",
       "std           74.178353      7.025483     9.118004e+06            10.600220   \n",
       "min            1.000000   1994.000000     1.000000e+00             0.000001   \n",
       "25%           55.000000   2000.000000     1.381700e+04             1.024000   \n",
       "50%          122.000000   2006.000000     2.533220e+05             5.762694   \n",
       "75%          176.000000   2012.000000     1.424034e+06            17.006000   \n",
       "max          514.000000   2018.000000     5.558942e+08           341.260000   \n",
       "\n",
       "       fuel_cost_per_unit_burned  fuel_cost_per_unit_delivered  \\\n",
       "count               29523.000000                  2.952300e+04   \n",
       "mean                  208.649031                  9.175704e+02   \n",
       "std                  2854.490090                  6.877593e+04   \n",
       "min                  -276.080000                 -8.749370e+02   \n",
       "25%                     5.207000                  3.778500e+00   \n",
       "50%                    26.000000                  1.737100e+01   \n",
       "75%                    47.113000                  4.213700e+01   \n",
       "max                139358.000000                  7.964521e+06   \n",
       "\n",
       "       fuel_cost_per_mmbtu  \n",
       "count         29523.000000  \n",
       "mean             19.304354  \n",
       "std            2091.540939  \n",
       "min             -41.501000  \n",
       "25%               1.940000  \n",
       "50%               4.127000  \n",
       "75%               7.745000  \n",
       "max          359278.000000  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame.describe(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.851495469109503"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Skewness\n",
    "pd.DataFrame.skew(data[\"fuel_qty_burned\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "651.3694501337732"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Kurtosis\n",
    "pd.DataFrame.kurtosis(data[\"fuel_qty_burned\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "67.42182999883"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z = data.groupby(\"fuel_type_code_pudl\")\n",
    "np.mean(z.get_group(\"coal\")[\"fuel_cost_per_unit_burned\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9196.705947610291"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z2 = data.groupby(\"report_year\")\n",
    "np.mean(z2.get_group(1996)[\"fuel_cost_per_unit_delivered\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20.56765451826053\n"
     ]
    }
   ],
   "source": [
    "z3 = data.groupby(\"fuel_type_code_pudl\")\n",
    "z4 = z3.get_group(\"coal\")\n",
    "z5 = z4.groupby(\"report_year\")\n",
    "x = np.sum(z5.get_group(1994)[\"fuel_cost_per_unit_burned\"])\n",
    "y = np.sum(z5.get_group(1998)[\"fuel_cost_per_unit_burned\"])\n",
    "print(x,y)\n",
    "print(((x-y)*100)/x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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",
       "        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>utility_id_ferc1</th>\n",
       "      <th>report_year</th>\n",
       "      <th>fuel_qty_burned</th>\n",
       "      <th>fuel_mmbtu_per_unit</th>\n",
       "      <th>fuel_cost_per_unit_burned</th>\n",
       "      <th>fuel_cost_per_unit_delivered</th>\n",
       "      <th>fuel_cost_per_mmbtu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>utility_id_ferc1</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.093323</td>\n",
       "      <td>-0.057447</td>\n",
       "      <td>-0.066946</td>\n",
       "      <td>-0.037863</td>\n",
       "      <td>-0.016414</td>\n",
       "      <td>0.006122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_year</th>\n",
       "      <td>0.093323</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012952</td>\n",
       "      <td>-0.110853</td>\n",
       "      <td>0.013599</td>\n",
       "      <td>-0.014043</td>\n",
       "      <td>0.010261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_qty_burned</th>\n",
       "      <td>-0.057447</td>\n",
       "      <td>0.012952</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.080946</td>\n",
       "      <td>-0.018535</td>\n",
       "      <td>-0.003551</td>\n",
       "      <td>-0.001896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_mmbtu_per_unit</th>\n",
       "      <td>-0.066946</td>\n",
       "      <td>-0.110853</td>\n",
       "      <td>-0.080946</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.010034</td>\n",
       "      <td>-0.009039</td>\n",
       "      <td>-0.005884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_cost_per_unit_burned</th>\n",
       "      <td>-0.037863</td>\n",
       "      <td>0.013599</td>\n",
       "      <td>-0.018535</td>\n",
       "      <td>-0.010034</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011007</td>\n",
       "      <td>-0.000437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_cost_per_unit_delivered</th>\n",
       "      <td>-0.016414</td>\n",
       "      <td>-0.014043</td>\n",
       "      <td>-0.003551</td>\n",
       "      <td>-0.009039</td>\n",
       "      <td>0.011007</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_cost_per_mmbtu</th>\n",
       "      <td>0.006122</td>\n",
       "      <td>0.010261</td>\n",
       "      <td>-0.001896</td>\n",
       "      <td>-0.005884</td>\n",
       "      <td>-0.000437</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              utility_id_ferc1  report_year  fuel_qty_burned  \\\n",
       "utility_id_ferc1                      1.000000     0.093323        -0.057447   \n",
       "report_year                           0.093323     1.000000         0.012952   \n",
       "fuel_qty_burned                      -0.057447     0.012952         1.000000   \n",
       "fuel_mmbtu_per_unit                  -0.066946    -0.110853        -0.080946   \n",
       "fuel_cost_per_unit_burned            -0.037863     0.013599        -0.018535   \n",
       "fuel_cost_per_unit_delivered         -0.016414    -0.014043        -0.003551   \n",
       "fuel_cost_per_mmbtu                   0.006122     0.010261        -0.001896   \n",
       "\n",
       "                              fuel_mmbtu_per_unit  fuel_cost_per_unit_burned  \\\n",
       "utility_id_ferc1                        -0.066946                  -0.037863   \n",
       "report_year                             -0.110853                   0.013599   \n",
       "fuel_qty_burned                         -0.080946                  -0.018535   \n",
       "fuel_mmbtu_per_unit                      1.000000                  -0.010034   \n",
       "fuel_cost_per_unit_burned               -0.010034                   1.000000   \n",
       "fuel_cost_per_unit_delivered            -0.009039                   0.011007   \n",
       "fuel_cost_per_mmbtu                     -0.005884                  -0.000437   \n",
       "\n",
       "                              fuel_cost_per_unit_delivered  \\\n",
       "utility_id_ferc1                                 -0.016414   \n",
       "report_year                                      -0.014043   \n",
       "fuel_qty_burned                                  -0.003551   \n",
       "fuel_mmbtu_per_unit                              -0.009039   \n",
       "fuel_cost_per_unit_burned                         0.011007   \n",
       "fuel_cost_per_unit_delivered                      1.000000   \n",
       "fuel_cost_per_mmbtu                              -0.000109   \n",
       "\n",
       "                              fuel_cost_per_mmbtu  \n",
       "utility_id_ferc1                         0.006122  \n",
       "report_year                              0.010261  \n",
       "fuel_qty_burned                         -0.001896  \n",
       "fuel_mmbtu_per_unit                     -0.005884  \n",
       "fuel_cost_per_unit_burned               -0.000437  \n",
       "fuel_cost_per_unit_delivered            -0.000109  \n",
       "fuel_cost_per_mmbtu                      1.000000  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame.corr(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "record_id                         0\n",
       "utility_id_ferc1                  0\n",
       "report_year                       0\n",
       "plant_name_ferc1                  0\n",
       "fuel_type_code_pudl               0\n",
       "fuel_unit                       180\n",
       "fuel_qty_burned                   0\n",
       "fuel_mmbtu_per_unit               0\n",
       "fuel_cost_per_unit_burned         0\n",
       "fuel_cost_per_unit_delivered      0\n",
       "fuel_cost_per_mmbtu               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6096941367747181\n"
     ]
    }
   ],
   "source": [
    "print(18000/len(data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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