- Maintainer: Scott Chamberlain
- License: MIT
- Report any problems in the Issues Tracker, or just fork and submit changes, etc.
rsunlight
is a collection of functions to search and acquire data from the various Sunlight Labs APIs for government data, at http://sunlightfoundation.com/api/.
rsunlight
wraps functions in APIs for:
- Congress API (
cg
) - Open States API (
os
) - Capitol Words API (
cw
) - Influence Explorer API (
ie
)
Functions that wrap these sets of APIs will be prefixed by cg
, os
, cw
, or ie
for the different methods listed above:
cg
+fxn
os
+fxn
cw
+fxn
ie
+fxn
where fxn
would be a function to a interface with a specific Sunlight Foundation API.
Please get your own API keys if you plant to use these functions for Sunlight Labs (http://sunlightfoundation.com/api/).
Data from the Sunlight Foundation API is provided by Sunlight Foundation.
We set up the functions so that you can put the key in your .Rprofile file, which will be called on startup of R, and then you don't have to enter your API key for each run of a function. For example, put this in your .Rprofile
file:
# key for API access to the Sunlight Labs API methods
options(SunlightLabsKey = "YOURKEYHERE")
Note that Puerto Rico is not included in Sunlight Foundation data.
If you store your key in your .Rprofile
file it will be read inside of each function call. Or you can pass your key into each function call manually by key=yourkey
.
From CRAN
install.packages("rsunlight")
Or development version from Github
install.packages("devtools")
library(devtools)
install_github("ropengov/rsunlight")
library("rsunlight")
cg_districts(latitude = 35.778788, longitude = -78.787805)
#> $results
#> state district
#> 1 NC 2
#>
#> $count
#> [1] 1
out <- cg_legislators(last_name = 'Reed')
Get a list of how many times the phrase "united states" appears in the Congressional Record in each month between January and June, 2010:
cw_timeseries(phrase='united states', start_date='2009-01-01', end_date='2009-04-30', granularity='month')
#> count month
#> 1 3805 2009-01-01
#> 2 3512 2009-02-01
#> 3 6018 2009-03-01
#> 4 2967 2009-04-01
library("ggplot2")
dat_d <- cw_timeseries(phrase='climate change', party="D")
dat_d$party <- rep("D", nrow(dat_d))
dat_r <- cw_timeseries(phrase='climate change', party="R")
dat_r$party <- rep("R", nrow(dat_r))
dat_both <- rbind(dat_d, dat_r)
ggplot(dat_both, aes(day, count, colour=party)) +
geom_line() +
theme_grey(base_size=20) +
scale_colour_manual(values=c("blue","red"))
Note that the resulting chart opens in a browser, so is not shown in this vignette, but you will see it open in a browser when you run the code.
dream <- lapply(c('D','R'), function(x) cw_timeseries(phrase='i have a dream', party=x, start_date='1996-01-01', end_date='2013-01-01', granularity='month'))
df <- merge(dream[[1]], dream[[2]], by='month', all=TRUE)
df[is.na(df)] <- 0
names(df) <- c('date','D','R')
df$date <- as.character(df$date)
library(rCharts)
m1 <- mPlot(x = "date", y = c("D", "R"), type = "Line", data = df)
m1$set(pointSize = 0, lineWidth = 1)
m1
note: as you can see this is not actually interactive, but when you make it, it will be
Ranked by total dollars given. An organization's giving is broken down into money given directly (by the organization's PAC) versus money given by individuals employed by or associated with the organization.
ie_industries(method='top_ind', limit=4)
#> count amount id
#> 1 14920003 3825328792.21 cdb3f500a3f74179bb4a5eb8b2932fa6
#> 2 3676565 2860383835.95 f50cf984a2e3477c8167d32e2b14e052
#> 3 1425026 1768144131.04 7500030dffe24844aa467a75f7aedfd1
#> 4 329908 1717719914.58 9cac88377c3b400e89c2d6762e3f28f6
#> should_show_entity name
#> 1 TRUE UNKNOWN
#> 2 TRUE LAWYERS/LAW FIRMS
#> 3 TRUE REAL ESTATE
#> 4 TRUE CANDIDATE SELF-FINANCE