# factor256

The goal of factor256 is to minimize the memory footprint of data analysis that uses categorical variables with fewer than 256 unique values.

## Installation

You can install the development version of factor256 from GitHub with:

## Example

This is a basic example which shows you how to solve a common problem:

```
library(data.table)
DT <-
CJ(Year = 2000:2020,
State = rep_len(c("WA", "SA", "NSW", "NT", "TAS", "VIC", "QLD"), 1000),
Age = rep_len(0:100, 10000))
# pryr::object_size(DT)
# 3.36GB
for (j in seq_along(DT)) {
set(DT, j = j, value = factor256(.subset2(DT, j)))
}
# pryr::object_size(DT)
# 630 MB
```