apitools: apitools

In donboyd5/apitools: Tools For Using the BEA and Census APIs

Description

Tools for using the APIs of the U.S. Bureau of Economic Analysis (BEA – www.bea.gov) and the Census Bureau (www.census.gov).

For information about the BEA API, see http://www.bea.gov/API/bea_web_service_api_user_guide.htm.

For details on BEA NIPA datasets see:

• NIPA: http://www.bea.gov/iTable/index_nipa.cfm

• NIPA underlying detail: http://www.bea.gov/iTable/index_UD.cfm

Overview

Basic steps for BEA data:

1. BEA_DSlist() to get a list of available datasets

2. Decide upon a dataset of interest

3. BEA_DSparams() to get the parameters needed for the dataset of interest

4. If you need information about allowable parameters, use BEA_ParamVals()

Example – NIPA data

bds <- BEA_DSlist() # get a list of available datasets
bds

BEA_DSparams("NIPA") # what parameters does the NIPA dataset require?
# note that Year=X gets all years - that is what is built into apitools
# TableID is the main parameter we need to know about; note that the API will NOT accept multiple TableIDs and it does not have AllValue

tablist <- BEA_ParamVals("NIPA", "TableID") # get a list of the available TableIDs
glimpse(tablist) # ok, we have to find the TableID of a BEA table we want
# assume we went to http://www.bea.gov/iTable/index_nipa.cfm and saw that Table 1.1.4. has the price indexes we want; now find it
filter(tablist, grepl("Table 1.1.4.", Description)) # TableID 4 has the info we want

nipadat <- NIPA_Data(4, "q") # get quarterly data from TableID 4, all years
head(nipadat)
count(nipadat, TableID, SeriesCode, LineNumber, LineDescription) # find all the variables

# we know from the above and from http://www.bea.gov/iTable/iTable.cfm?ReqID=9&step=1#reqid=9&step=3&isuri=1&903=4 that LineNumber 26 has the price index for State & local government consumption
slgpi <- nipadat tail(slgpi)

Example – get multiple NIPA tables

# Start by getting a vector of TableIDs based on their BEA formal Table names

nipatabvec <- c("2.1", "2.3.4", "2.3.6", "3.3", "3.9.6", "3.10.6")
df <- NIPA_DataMult(nipatabvec) # this can take a while
head(df)
count(df2, TableID, Description)

donboyd5/apitools documentation built on May 15, 2019, 10:38 a.m.