flexdash1.Rmd

---
title: "UNHCR Livelihoods Data 2019 - Major crops yield and family size"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
---

```{r setup, include=FALSE}
### Author: Abel Gelman
### 4-  static dashboard

library(flexdashboard)
library(ggplot2)
library(plotly)
library(plyr)
library(tidyverse)

drs_df_raw_link <- "https://raw.githubusercontent.com/CartONG/R_training/main/df19.csv?token=ALMJAS5FZNUMPT2YXW2HM23A4B6Z2"

# download file again but forcing R to read all columns as character
df19 <- read_csv(drs_df_raw_link,
                 col_types = cols(.default = "c"))



```

Column {data-width=350}
-----------------------------------------------------------------------

### Yield per family size: CASSAVA

```{r}
df19$Crop1KG <- as.numeric(df19$Crop1KG)
df19$Crop1HA <- as.numeric(df19$Crop1HA)
df19$FamilySize <- as.numeric(df19$FamilySize)


dfYield3 <- df19 %>%
  select(BE, Country, FamilySize, Crop1, Crop1HA, Crop1KG, O1IncomeFarming, ArrivalYear) %>% 
  mutate(Yield = round(Crop1KG / Crop1HA, 0),
         Check = Yield < 150) %>% 
  filter(Check==FALSE) %>% 
  filter (Crop1=="Cassava"|Crop1=="Maize"|Crop1=="Groundnuts, with shell") %>% 
  filter(Yield != Inf)

dfYield_cassava <- dfYield3 %>% 
  filter(Yield < 5000 & FamilySize < 15) %>% 
  filter(Crop1 == "Cassava") %>% 
  ggplot(aes(x = FamilySize, y = Yield))+
  geom_point(colour = "green", alpha = 0.3)+
  geom_jitter(height = 0.2, width = 0.4, colour = "green", alpha = 0.3)

ggplotly(dfYield_cassava)
#rm(dfYield_cassava)

```

Column {data-width=350}
-----------------------------------------------------------------------

### Yield per family size: GROUNDNUTS

```{r}


dfYield_groundnuts <- dfYield3 %>% 
  filter(Yield < 5000 & FamilySize < 15) %>% 
  filter(Crop1 == "Groundnuts, with shell") %>% 
  ggplot(aes(x = FamilySize, y = Yield))+
  geom_point(colour = "red", alpha = 0.3)+
  geom_jitter(height = 0.2, width = 0.4, colour = "red", alpha = 0.3)

ggplotly(dfYield_groundnuts)

```

### Yield per family size: MAIZE

```{r}
dfYield_Maize <- dfYield3 %>% 
  filter(Yield < 5000 & FamilySize < 15) %>% 
  filter(Crop1 == "Maize") %>% 
  ggplot(aes(x = FamilySize, y = Yield))+
  geom_point(colour = "blue", alpha = 0.3)+
  geom_jitter(height = 0.2, width = 0.4, colour = "blue", alpha = 0.3)


ggplotly(dfYield_Maize)

```