tidyverse_create_covidpolls.Rmd

---
title: "Tidyverse Create Assignment"
author: "Claire Meyer"
date: "3/28/2021"
output: html_document
---

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

## Summary

This document will take some aggregated polling data from FiveThirtyEight, use TidyR to clean it up, and ggplot to do some lightweight plotting.

Details on data found [here](https://github.com/fivethirtyeight/covid-19-polls).

### Loading Data and filtering with Dplyr

To start, we'll load the Tidyverse library, download the polling_data, and do some clean-up. I'll use dplyr's filter to filter for polls of the voting population (population == 'rv').

```{r load}
library(tidyverse)

polling_data <- read.csv("http://raw.githubusercontent.com/fivethirtyeight/covid-19-polls/master/covid_approval_polls.csv", header=TRUE) %>%
  filter(population == 'rv')
```

### Changing the shape of the data with TidyR

I want to use Tidyr to change the shape of this data. I want to make this data wider. Right now it has at least 4 rows per poll, with each party (R, D, I) as well as an 'all' aggregated category. 

```{r make-wider}
polling_data_wide <- polling_data %>%
  pivot_wider(names_from = 'party',values_from = c('approve','disapprove','sample_size'))
```

### Plotting with ggplot

I want to make a quick plot of 'R' approval ratings of Trump and Biden.

```{r plotting}
ggplot(polling_data_wide, aes(x=approve_R))+
  geom_histogram()+ facet_grid(subject ~ .)
```