README.Rmd

---
output: github_document
---

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

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# lookupr

Lookup pulls common lookup tables from the [lookup](https://github.com/wireservice/lookup) repository and joins them to your data.

This is a port of Python's [agate-lookup](https://agate-lookup.readthedocs.io).

This version does not do caching. If you don't want to redownload lookup tables, save a local copy of your results.

## Install

From Github:

``` r
install.packages("devtools")
devtools::install_github("wireservice/lookupr")
```

## Usage

Load libraries:

```{r, message = FALSE}
library(dplyr)
library(lookupr)
```

Lookup the consumer price index for yearly data:

```{r}
data <- data.frame(year = c("2004", "2005", "2006", "2007"))

data %>%
  lookup("year", "cpi")
```

If you're column name is different from `year`:

```{r}
data <- data.frame(anum = c("2004", "2005", "2006", "2007"))

data %>%
  lookup("anum", "cpi", lookup_keys = "year")
```

Monthly CPI:

```{r}
data <- data.frame(
  year = c("2004", "2004", "2005", "2005"),
  month = c("11", "12", "1", "2")
)

data %>%
  lookup(c("year", "month"), "cpi", version="sa")
```

## Inflation adjustment

As it's such a common use-case, lookup includes shortcut functions for doing CPI adjustment:

```{r}
data <- data.frame(
  year = c("2005", "2006", "2007", "2008", "2009", "2010"),
  price_a = c(100, 100, 100, 100, 100, 100),
  price_b = c(200, 200, 200, 200, 200, 200)
)

data %>%
  lookup_cpi(c("price_a", "price_b"), base = "2010")
```