---
title: "Categorical Data"
author: "Aravind Hebbali"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Categorical Data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r, echo=FALSE, message=FALSE}
library(descriptr)
library(dplyr)
```

## Introduction

In this document, we will introduce you to functions for exploring and 
visualizing categorical data.

## Data

We have modified the `mtcars` data to create a new data set `mtcarz`. The only
difference between the two data sets is related to the variable types. 

```{r egdata}
str(mtcarz)
```

## Cross Tabulation

The `ds_cross_table()` function creates two way tables of categorical variables. 

```{r cross}
ds_cross_table(mtcarz, cyl, gear)
```

If you want the above result as a tibble, use `ds_twoway_table()`.

```{r cross_tibble}
ds_twoway_table(mtcarz, cyl, gear)
```

A `plot()` method has been defined which will generate:

### Grouped Bar Plots

```{r cross_group, fig.width=7, fig.height=7, fig.align='centre'}
k <- ds_cross_table(mtcarz, cyl, gear)
plot(k)
```

### Stacked Bar Plots

```{r cross_stack, fig.width=7, fig.height=7, fig.align='centre'}
k <- ds_cross_table(mtcarz, cyl, gear)
plot(k, stacked = TRUE)
```

### Proportional Bar Plots

```{r cross_prop, fig.width=7, fig.height=7, fig.align='centre'}
k <- ds_cross_table(mtcarz, cyl, gear)
plot(k, proportional = TRUE)
```

## Frequency Table 

The `ds_freq_table()` function creates frequency tables.

```{r ftable}
ds_freq_table(mtcarz, cyl)
```

A `plot()` method has been defined which will create a bar plot.

```{r ftable_bar, fig.width=7, fig.height=7, fig.align='centre'}
k <- ds_freq_table(mtcarz, cyl)
plot(k)
```

## Multiple One Way Tables

The `ds_auto_freq_table()` function creates multiple one way tables by creating a 
frequency table for each categorical variable in a data set. You can also 
specify a subset of variables if you do not want all the variables in the data 
set to be used.

```{r oway}
ds_auto_freq_table(mtcarz)
```

## Multiple Two Way Tables

The `ds_auto_cross_table()` function creates multiple two way tables by creating a 
cross table for each unique pair of categorical variables in a data set. You 
can also specify a subset of variables if you do not want all the variables in 
the data set to be used.

```{r tway}
ds_auto_cross_table(mtcarz, cyl, gear, am)
```