Description

rcicero is a bouquet of functions to query the Cicero API, a useful tool for data on elected officials. Be sure to check Cicero's Terms of Use prior to installation.

Required Packages

rcicero requires three packages under the hood: httr, dplyr, and tidyjson. If you work with nested JSON on a semi-regular basis, I highly recommend tidyjson.

Installation

rcicero is not on CRAN, but can be installed via:

devtools::install_github("daranzolin/rcicero")
library(rcicero)

Setup

Some prep work is required before usage. The API requires three parameters: (1) an API key; (2) a user id; and (3) an API token. First, create an account and obtain your API key in your profile. Creating an account is free, and you will be granted 1000 free credits (1 credit per query). Further use will require the purchase of additional credits.

Once you obtain your key, run:

set_token_and_user("your_account_email_address", "your_password")
[1] "Your Cicero API user and token options have been set."

Behind the scenes, rcicero stashes the user and token values into your global options. You must then add the key to your .Renviron, as "CICERO_API_KEY". For help on setting up your .Renviron (and everything else R-related) see Jenny Bryan's Stat545 page. Warning: the API token expires every 24 hours.

Usage

Four functions make the bulk of rcicero: get_legislative_district(), get_official(), get_nonlegislative_district(), and get_upcoming_elections(). Each returns a data.frame object, with the exception of get_official(), which returns a list.

### Get legislative district data:
santa_clara <- get_legislative_district(seach_loc = "3175 Bowers Ave. Santa Clara, CA")

### Get official data:
### By name
lewis <- get_official(first_name = "John", last_name = "Lewis", district_type = "NATIONAL_LOWER")

### By lat/lon coordinates:
o <- get_official(lat = 40, lon = -75.1)

###Get upcoming elections:
e <- get_upcoming_elections(is_state = TRUE, elections = 4)

###Get non-legislative district information
nld <- get_nonlegislative_district(search_loc = "3175 Bowers Ave. Santa Clara, CA", type = "SCHOOL")

### Get map data (work in progress)
map <- get_map(state = "CA", district_type = "NATIONAL_LOWER", district_id = 5)

Future Work