Coder Social home page Coder Social logo

censusdata's Introduction

NOTE: as of March 28, 2022, I am unable to continue providing updates to this package. While it should still work for the release years it was originally written for, I cannot guarantee that. The code is freely available for modification as needed for the years the package was written for, or to add support for more recent years of data.

This package is designed to provide easy access to the U.S. Census Bureau's API (https://www.census.gov/developers/) in Python. It supports pulling data from the American Community Survey (ACS) and the Census Summary File, specifically:

  • ACS 5-year estimates (2005-2009 to 2015-2019),
  • ACS 1-year estimates (2012-2019),
  • ACS 3-year estimates (2010-2012 to 2011-2013),
  • ACS 1-year supplemental estimates (2014-2019),
  • Census 2010 Summary File 1.

This package handles the details of interacting with the Census API for you, so that you can focus on working with the data. It provides a class for representing Census geographies. It also provides functions for gaining further information about specific variables and tables and for searching for variables. Full documentation is available at https://jtleider.github.io/censusdata/.

The ACS (https://www.census.gov/programs-surveys/acs/) started in 2005. It provides information on a wide range of social, economic, demographic, and housing characteristics. Topics covered include income, employment, health insurance, the age distribution, and education, among many others. The ACS replaces the old Census long form, which used to be distributed to a subset of households responding to the decennial Census. The ACS produces survey-based period estimates. For instance, the 5-year 2011-2015 estimates are based on data collected during all 5 years. They are not simply an aggregate of 1-year estimates, and overlapping 5-year estimates (e.g., 2008-2012 and 2011-2015) should not be compared. The ACS provides margins of error to accompany all estimates. Margins of error are smaller for estimates based on more years of data.

ACS 5-year estimates are the least current but provide the greatest precision and are available for geographies of all sizes (https://www.census.gov/programs-surveys/acs/guidance/estimates.html). By contrast, 1-year estimates are the most current but the least precise and are only available for geographies with populations of 65,000+. In between are the 1-year supplemental estimates or, in past years, the 3-year estimates, both of which are for geographies with populations of 20,000+. The choice of which ACS estimates to use will depend on your needs for current data vs. data for a variety of geographies with greater precision.

The decennial Census counts every resident of the United States. The 2010 Census Summary File 1 provides information about each community's population, including age, sex, and race distributions, as well as information on households and families. (Summary File 2 provides additional data for specific racial/ethnic groups.)

There are a number of facilities available for downloading Census data, including American FactFinder, the ACS summary files, and the Census DataFerrett. This package is designed to provide the following features not available elsewhere:

  • Easy download of specific variables across a variety of tables, downloading only the variables you need for the geographies of interest to you. This bypasses data processing hassles associated with working with other sources like the ACS Summary Files.
  • Access to the exact variables of interest, with variable names making it easy to look up further information on the source tables or to pull up other years of data. This facilitates work by more technical users.
  • Download data for multiple geographies at once, such as all counties in the United States, or all block groups in Illinois.
  • Work with the data as a Pandas data frame, or export to CSV for analysis in other data analysis packages.

censusdata's People

Contributors

jtleider avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.