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A Baltimore Sun analysis of data from the 2013-17 American Community Survey (ACS) and the Small Area Income Poverty Estimates (SAIPE) program for 2017.

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Census data analysis: ACS and SAIPE

By Christine Zhang

An analysis of data from the 2013-17 American Community Survey (ACS) and the Small Area Income Poverty Estimates (SAIPE) program for a December 7, 2018 Baltimore Sun story titled "What new Census data reveal about wealth, diversity, and connectivity in Maryland".

The code used to produce the analysis is saved in a series of six notebooks.

Each notebook corresponds to a topic in the story. For example, 04_broadband_acs.ipynb refers to the findings under the section referring to broadband connectivity, "Maryland rates well nationally for broadband connectivity, but Baltimore and the state's western- and southern-most counties lag."

We used tidycensus by Kyle Walker and censusapi by Hannah Recht to access the Census Bureau API in R.

https://twitter.com/baltsundata

Community Contributions

There are many angles to explore with this data.

Have something to contribute? Send us a pull request or contact us on Twitter @baltsundata or via email

You can also fork a copy of this repo to your own account.

Licensing

All code in this repository is available under the MIT License. The data files are available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

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A Baltimore Sun analysis of data from the 2013-17 American Community Survey (ACS) and the Small Area Income Poverty Estimates (SAIPE) program for 2017.

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