---
title: "Report targetpct"
author: "Roland Krasser"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Report target%}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

Automated Exploratory Analysis (auto EDA) using the `report()` function of the explore package.

In this example we use synthetic data created by the `create_data_churn()`function of the explore package.

```{r echo=TRUE, message=FALSE, warning=FALSE}
library(dplyr)
library(explore)
data <- create_data_churn()
```

Then we generate the report.

```{r eval=FALSE}
data %>% report(target = churn, targetpct = TRUE, output_dir = tempdir())
```

# Explore

## Describe Data

```{r fig.height=3, fig.width=6, echo=FALSE, message=FALSE, warning=FALSE}
data %>% explore_tbl()
```

```{r echo=FALSE, message=FALSE, warning=FALSE}
data  %>%  describe_tbl()
```

```{r echo=FALSE, message=FALSE, warning=FALSE}
describe(data)
```

## Describe Target

```{r fig.height=3, echo=FALSE, fig.height=3, fig.width=5, message=FALSE, warning=FALSE}
data %>% explore(churn)
```

## Explore Variables

```{r include=FALSE}
# create buckets of variables
buckets <- data  %>%  
  explore::get_var_buckets(
    bucket_size = 100
  )

# height of each plot
fig_height <- data[buckets[[1]]]  %>%  
  explore::total_fig_height(size = 2)

```

```{r echo=FALSE, fig.height=fig_height, fig.width=7, message=FALSE, warning=FALSE}
for (i in seq_along(buckets)) {
  data[buckets[[i]]]  %>%  
    explore_all(target = churn, targetpct = TRUE, ncol = 2)
} 
```
