This page gives information on how to use the
Before you begin working with the US Census API, you need to obtain an API key. This can be done here. I recommend putting your API key in a config.py file and adding this file to your
.gitignore so that your key is saved offline if you intend on saving your results on Github.
To use the
census_api package, start by importing the library and the config file in which you placed your API key. In your working file, create an instance of the
CensusQuery class. This requires you to pass your API key and a string identifying the dataset you would like to query. As of now, we only support querying the ACS1 (
"acs1"), ACS5 (
"acs5"), and SF1 (
"sf1") datasets. You can optionally also pass a year and an output type to the class instance.
import config import census_api c = CensusQuery(config.api_key, "acs5", year=2016)
If you don't pass a year to the
CensusQuery instance, you must pass it when you call
CensusQuery.query. If you do pass a year, the year argument is optional in
CensusQuery.query, but if it is passed, the instance variable will be ignored in favor of the year passed to
To actually query the API, you must call
CensusQuery.query. The required arguments are the list of variables to extract and the state (as its 2-letter abbreviation). You can also narrow your results by optionally passing a county name and a tract FIPS code, but these are not required. If they are not passed, the query returns all counties and all tracts. There is also an optional year argument, discussed in the previous paragraph.
c.query(["NAME", "B00001_001E", "B01001_002M", "B06007PR_031E"], "CA")
If we wanted only tract 4010 of Alameda County in 2014, the call would be
c.query(["NAME", "B00001_001E", "B01001_002M", "B06007PR_031E"], "CA", county="Alameda", tract="4010", year=2014)
For more information on the variables, see the Census API documentation. This page lists all of the data sets by year, so find the year and dataset that you are looking for and then click on "variables" in its row.
This package supports rendering outputs in two forms: as a
pandas DataFrame or as a
datascience Table. The class defaults to a DataFrame, but this is overridden by passing the optional
out argument when creating the
CensusQuery instance. This argument defaults to the string
"pd", but if
"ds" is passed instead, the outputs will be Tables rather than DataFrames.
ds_c = CensusQuery(config.api_key, "acs5", year=2016, out="ds")
For more information on how to use the package, launch our Binder.