---
title: "Pepe Vignette"
author: "Seyma Kalay"
data: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Pepe Vignette}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

```{r setup}
library(pepe)
```


This package was set for the data visualization. 
First thing let's see the str of the *sample_data* with `str(sample_data)`. 

`Plot.by.Factr` function will create plotting.

```{r plot ,  fig.width= 7, echo=TRUE}
df <- sample_data[c("Formal","Informal","L.Both","No.Loan",
"sex","educ","political.afl","married",
 "havejob","rural","age","Income","Networth","Liquid.Assets",
 "NW.HE","fin.knowldge","fin.intermdiaries")]
 CN = colnames(df)
 var <- c("educ","rural","sex","havejob","political.afl")
 name.levels = c("Formal","Informal","L.Both","No.Loan",
 "sex","educ","political.afl","married",
 "havejob","rural","age","Income","Networth","Liquid.Assets",
 "NW.HE","fin.knowldge","fin.intermdiaries")

XXX <- df4.Plot.by.Factr(var,df)$Summ.Stats.long
Plot.by.Factr(XXX, name.levels)

```


`df4.Plot.by.Factr` function will create group stats.

```{r df4plot, echo=TRUE}
df4.Plot.by.Factr(var,df)

```

`Stats.by.Factr` function will create group stats.

```{r statsfactr, echo=TRUE}
 Stats.by.Factr(var, df)
```



`Pvot.by.Factr` function will create a percentage tables.
```{r pvotfactr, echo=TRUE}
df <- sample_data[c("multi.level",
"Formal","L.Both","No.Loan",
 "region", "sex", "educ", "political.afl",
 "married", "havejob", "rural",
 "fin.knowldge", "fin.intermdiaries")]
 Pvot.by.Factr(df)
```
