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README.Rmd
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---
output:
github_document:
html_preview: false
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r message=FALSE, include=FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
options(tibble.print_min = 5, tibble.print_max = 5, tibble.max_extra_cols = 5)
library(geoclient)
```
# geoclient
[](https://travis-ci.org/austensen/geoclient)
[](https://ci.appveyor.com/project/austensen/geoclient)
[](https://codecov.io/github/austensen/geoclient?branch=master)
[](https://www.tidyverse.org/lifecycle/#maturing)
Tools to work with NYC's _Geoclient_ REST API.
This packages uses NYC's Geoclient API but is neither endorsed nor supported
by the the City of New York.
For information about the Geoclient API visit
[NYC's Developers Portal](https://developer.cityofnewyork.us/api/geoclient-api).
### Installation
Install from Github with [remotes](https://github.com/r-lib/remotes):
```{r eval=FALSE, include=TRUE}
# install.packages("remotes")
remotes::install_github("austensen/geoclient")
```
### Set up _Geoclient_ API keys
You can acquire your Geoclient app ID and Key by first registering with the
[NYC's Developer Portal](https://developer.cityofnewyork.us/user/register?destination=api)
at, then [create a new project](https://developer.cityofnewyork.us/create/project),
selecting "Geoclient v1" from available APIs.
To avoid having to provide the ID and Key with each function call you can use `geoclient_api_keys()` to add your Geoclient app ID and Key to your `.Renviron` file
so they can be called securely without being stored in your code.
```{r eval=FALSE, include=FALSE}
library(geoclient)
geoclient_api_keys("xxx", "xxx")
```
### Basic Usage
There are 6 main location types that can be set with _Geoclient_: Address, BBL (Borough-Block-Lot), BIN (Building Identification Number), Blockface, Intersection, and Place ("well-known NYC place name"). All of these functions return the results of the _Geoclient_ API call as a dataframe, with additional columns for the arguments provided to the function.
```{r}
geo_address(
house_number = "139",
street = "MacDougal St",
borough = "MN",
zip = "10012"
)
```
You can also pull out just a single column if that is all you need.
```{r}
df <- tibble::tribble(
~num, ~st, ~boro, ~zip,
"139", "MacDougal St", "manhattan", "11231",
"295", "Lafayette street", NA, "10012-2722",
"40", "WASHINGTON SQ S", "MN", NA
)
dplyr::mutate(df, bbl = geo_address(num, st, boro, zip)[["bbl"]])
```
For each of these location types there are two functions in this package that allow the arguments to be supplied either as individual vector, or with a dataframe and bare column names.
```{r}
geo_address_data(df, num, st, boro, zip)
```
The return dataframe will always be the same length and in the same order, so you can easily add all the return columns to your existing dataframe.
```{r}
dplyr::bind_cols(df, geo_address_data(df, num, st, boro, zip))
```
In addition to the 6 location types, _Geoclient_ also provides a single-field search option, which will guess the location type. This can be particularly helpful when you have address data that is not easily separated for use with `geo_address()`.
```{r}
df <- tibble::tribble(
~address,
"139 MacDougal St manhattan, 11231",
"295 Lafayette street, 10012-2722",
"40 WASHINGTON SQ S MN"
)
geo_search_data(df, address)
```