---
title: "Plotting Water Data"
author: "John Fay"
date: "9/17/2019"
output: html_document
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# Plotting with ggplot

## Import packages
```{r message=FALSE, warning=FALSE}
library(tidyverse)
library(ggplot2)
```


## Read in the data
```{r Read in the data}
water.data <- readxl::read_excel('./data/State_Data_Formatted.xlsx','WaterUse')
str(water.data)

popn.data <- readxl::read_excel('./data/State_Data_Formatted.xlsx','Population')
str(popn.data)
```

```{r fix Withdrawal data type}
water.data$Withdrawal_MGD <- as.double(water.data$Withdrawal_MGD)
str(water.data)
```


## Join the tables
```{r}
all.data <- inner_join(water.data,
                       popn.data,
                       by=c("State"= "STATE"))
```


## Construct the visualization

### Basic plot
```{r Basic plot}
g <- ggplot(water.data) 
g + geom_col(aes(x=Category, y=Withdrawal_MGD))
```

### Aesthetics: _fill_
```{r Basic plot with fill aes}
g <- ggplot(all.data) 
g + geom_col(aes(x=Category, 
                 y=Withdrawal_MGD,
                 fill=Source))
```


### Facets: _facet_grid_
```{r Facet plot}
ggplot(all.data) +
 geom_col(aes(x=Category, 
                y=Withdrawal_MGD,
                fill=Source)) +
 facet_grid(facets=.~Type)
```


### Labels and coordinate systems
```{r Lables and rotated}
ggplot(data=all.data) + 
 geom_col(aes(x=Category,
              y=Withdrawal_MGD,
              fill=Source)) + 
 facet_grid(facets=.~Type) +
 ggtitle('Per capita water withdrawals') + 
 ylab("Per capita water withdrawals (MGD/person)") +
 coord_flip()
```

### Filtering and sorting
```{r Filter to remove "Total" and keep only "Fresh"}
subset.data <-  filter(all.data, Category != "Total" & Type == "Fresh")
subset.data$Category = as.factor(subset.data$Category)
str(subset.data)
```

```{r Add a sorted factor list}
#Convert the Category variable to a factor
subset.data$Category = as.factor(subset.data$Category)
#Sort base onm this category
subset.data$Category <-  fct_reorder(.f=subset.data$Category,       #Sort the Category values
                                     .x=subset.data$Withdrawal_MGD, #...based on values in the Withdrawal_MGD column
                                     .fun=sum)                      #...using their grouped sums
#Reverse the sort order
subset.data$Category <- fct_rev(subset.data$Category)
```


```{r Plot the sorted data}
ggplot(data=subset.data) + 
 geom_col(aes(x=Category,
              y=Withdrawal_MGD,
              fill=Source)) + 
 facet_grid(facets=.~Type) +
 ggtitle('Per capita water withdrawals') + 
 ylab("Per capita water withdrawals (MGD/person)") +
 coord_flip()
```

## Export the image
```{r Export}
#Create the plot
p <- ggplot(data=subset.data) + 
       geom_col(aes(x=Category,
                    y=Withdrawal_MGD,
                    fill=Source)) + 
       facet_grid(facets=.~Type) +
       ggtitle('Per capita water withdrawals') + 
       ylab("Per capita water withdrawals (MGD/person)") +
       coord_flip()

#Save the plot
ggsave(filename="PlotFrom_R.png",plot=p,width=10,heigh=3)
```