---
title: "mtb: Summary from Multiple Tables"
author: "Y. Hsu"
date: '`r Sys.Date()`'
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{mtb: Summary from Multiple Tables}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

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

## Background

Assume that for each month, items purchased in each grocery store visit 
are recorded in a table.
At the end of a year, we may want to generate a summary table that shows 
how many times each item being purchased over the year and 
also list some summary statistics.

## How to use

This is a basic example which shows you how to summarize item frequency
from multiple tables.

```{r example_1}
library(mtb)
head(exdt[[1]])
```

This is a basic example which shows you how to create a cross-count table: 

```{r example_2}

head(bill_cross_count(exdt[1:6], id='name', gp=c('category1'), type = 'count' ) )

```

This is a basic example which shows you how to create a cross-count table with conditions: 

```{r example_3}

head(bill_cross_count(exdt[1:6], id='name', gp=c('category1'), type = 'cond', condstr='store==2' ) )

```

This is a basic example which shows you how to create a cross-count table with conditions and total: 

```{r example_4}

head(bill_cross_count(exdt[1:6], id='name', gp=c('category1'), type = 'condwt', condstr='store==1' ) )

```

This is a basic example which shows you how to cross-check differences in two table: 

```{r example_5}

head(bill_cross_check(exdt[[1]], exdt[[2]], id=c('category1', 'name','store') ) )

```

