Using Data.gov APIs in R

# Set working directory 
setwd('~/DataApiR') # plug in the working directory on your machine

# Load package
library(httr)

# plug in your API key
myapikey <- "YOUR API KEY"

# the url path to the service
URL <- "https://api.data.gov/ed/collegescorecard/v1/schools?"

# GET(): download all available data for Emory University
get.data <- GET(URL, query=list(api_key=myapikey,
                                  school.name="Emory University"))

# content(): extract the content from the query
emory.data <- content(get.data)
class(emory.data) # it's a list object

# what's in emory.data
names(emory.data) # contains two components: metadata, results

# what's inside the results component
names(emory.data$results[[1]])

# see available dev-categories for 2013 data
names(emory.data$results[[1]]$`2013`)

# available variables under the cost category for 2013 data
names(emory.data$results[[1]]$`2013`$cost)

# elements of the tuition variable
names(emory.data$results[[1]]$`2013`$cost$tuition)

# load package
library(magrittr)

# subset list for annual data only
emory.ann <- emory.data$results[[1]][c(as.character(1996:2013))]
names(emory.ann)

# extract enrollment of undergraduate degree-seeking students for each year
s.size <- emory.ann %>%
    sapply(function(x) x$student$size) %>%
    unlist()

# extract percentage of first-generation students for each year
s.fg <- emory.ann %>%
    sapply(function(x) x$student$share_firstgeneration) %>%
    unlist()

# combine the two variables into a data frame
emory.s <- data.frame(s.size, s.fg)

# see the first few rows of the data frame
head(emory.s)

# create a variable of year from the row number
emory.s$year <- rownames(emory.s)

# create a variable s.fg.n: number of first-generation students
emory.s$s.fg.n <- round(emory.s$s.size*emory.s$s.fg)

# save the data as a .csv file
write.csv(emory.s, file="emory.s.csv", row.names = F)

# load package
library(ggplot2)

# Line graph of total enrollment and first generation student number
ggplot(emory.s, aes(year)) + 
    geom_line(aes(y = s.size, colour = "s.size", group=1)) + 
    geom_line(aes(y = s.fg.n, colour = "s.fg.n", group=1)) +
    xlab("Year") + ylab("Number") + # Set axis labels
    ggtitle("Enrollment: Emory University") + # set title      
    scale_colour_discrete(name="Enrollment",  # modify legend
                          labels=c("First Generation", "Total")) +
    theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5)) # adjust x-axis text position

library(rscorecard)
sc_key('YOUR API KEY')

# extract Virginia institutions' 2013 data with three variables
df <- sc_init() %>%
    sc_filter(stabbr == 'VA') %>%
    sc_select(unitid, instnm, stabbr) %>%
    sc_year(2013) %>%
    sc_get()

# see first few cases
head(df)

# load packages
library(httr)
library(magrittr)
library(ggplot2)

# Get all stations data in Virginia, remember to plug in your own API key
get.afs <- GET("http://api.data.gov/nrel/alt-fuel-stations/v1.json?api_key=[YOUR API KEY]&state=VA")

# extract content from the query
afs <- content(get.afs)

# see what's available in the downloaded data
names(afs)

# how many stations in the downloaded data
afs$total_results

# see variables/fields under fuel_stations
names(afs$fuel_stations[[1]])

# extract vars: station_name, fuel_type_code
fsname <- afs$fuel_stations %>%
    sapply(function(x) x$station_name) %>%
    unlist()
ftcode <- afs$fuel_stations %>%
    sapply(function(x) x$fuel_type_code) %>%
    unlist()

# combine the two vars in a data frame
afsdf <- data.frame(fsname, ftcode)

# see the first few rows
head(afsdf)

# plot ftcode: type of alternative fuel the station provides
ggplot(afsdf, aes(x=ftcode)) +
    geom_bar(stat="count", fill="steelblue") +
    theme_minimal()