README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# censable <img src='man/figures/logo.png' align="right" height="139" />
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`censable` wraps `censusapi` for common requests, with [memoized](https://github.com/r-lib/memoise) data functions. With a growing redistricting universe in R, it seems right to partition out some use cases, to allow imports to be more targeted and to stop packages from repeating each other.

## Installation

You can install the released version of censable from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("censable")
```
You can download the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("christopherkenny/censable")
```
## Example
```{r}
library(censable)
```

The primary data functions are `build_dec` and `build_acs`
```{r, results='hide'}
de <- build_dec(geography = 'county', state = 'DE')
```
The `build_*` functions take arguments on geography and state, at a minimum. If you're looking at a smaller piece of a state, you can use `county` to subset it. Year defaults to 2010, but will be updated to 2020 around October 2021, following the API release of the 2020 Census data.

The `build_*` functions are a convenient wrapper around `censusapi`, with an eye towards collecting data on total population and voting age population by race. Total population variables begin with the prefix `pop`, while voting age population variables begin with the prefix `vap`. 

Additionally, there are memoised versions of the `build_*` functions:
```{r, results='hide'}
de <- mem_build_dec(geography = 'county', state = 'DE')
```
These speed up repeated calls, allowing you to have code that is self contained and reproducible, without taking the time hit of having to re-download the data each time.