Census Data Workflow using IPUMS NHGIS API: Data Request and Download
Principal Investigator(s): View help for Principal Investigator(s) Wayne Day, Texas A&M University; Cooper Goodman, Texas A&M University; Donghwan Gu, Texas A&M University; Jayasaree Korukonda, Texas A&M University; Nathanael Rosenheim, Texas A&M University
Version: View help for Version V1
| Name | File Type | Size | Last Modified |
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| NHGIS_2_getdata_2020-07-29 | 07/31/2020 12:40:PM | ||
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text/plain | 1.4 MB | 07/29/2020 08:24:AM |
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application/pdf | 2.2 MB | 07/31/2020 08:23:AM |
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text/plain | 103.4 KB | 07/29/2020 08:29:AM |
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application/pdf | 391.9 KB | 07/31/2020 08:30:AM |
Project Citation:
Day, Wayne, Goodman, Cooper, Gu, Donghwan, Korukonda, Jayasaree, and Rosenheim, Nathanael. Census Data Workflow using IPUMS NHGIS API: Data Request and Download. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-07-31. https://doi.org/10.3886/E120305V1
Project Description
Summary:
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This archive provides two Jupyter Notebooks to explore metadata and retrieve data using the IPUMS NHGIS API. American Community Survey (ACS) 5-year estimates 2005-2009 at the block group and county levels are requested and downloaded for Galveston County, Texas. Data of interest are race and ethnicity, and median household income. Block group and county shapefiles are also downloaded.
The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration and management.The notebooks use Google Drive for file storage and include extensive markdown and comments. The notebooks can be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive).
The first notebook explores metadata in order to identify relevant datasets and tables and necessary parameters for subsequent data request and retrieval. The second notebook uses the parameters identified from the first notebook. A data request is constructed and the data extract is downloaded and files unzipped and made ready for analysis. The data that were downloaded are also stored separately with this archive.
The data referenced in this archive have research applications listed in the Related Publications section and in ongoing research at the Texas A&M University Department of Landscape Architecture and Urban Planning (LAUP), and the Hazard Reduction and Recovery Center (HRRC).
The Python code was developed in Google Colaboratory, or Google Colab for short, which is an Integrated Development Environment (IDE) of JupyterLab and streamlines package installation, code collaboration and management.The notebooks use Google Drive for file storage and include extensive markdown and comments. The notebooks can be adapted for use in other environments (i.e., Jupyter Notebook) as well as reading and writing files to a local or shared drive, or cloud drive (i.e., Google Drive).
The first notebook explores metadata in order to identify relevant datasets and tables and necessary parameters for subsequent data request and retrieval. The second notebook uses the parameters identified from the first notebook. A data request is constructed and the data extract is downloaded and files unzipped and made ready for analysis. The data that were downloaded are also stored separately with this archive.
The data referenced in this archive have research applications listed in the Related Publications section and in ongoing research at the Texas A&M University Department of Landscape Architecture and Urban Planning (LAUP), and the Hazard Reduction and Recovery Center (HRRC).
Funding Sources:
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National Institute for Standards and Technology (70NANB15H044);
National Institute for Standards and Technology (70NANB20H008);
Texas A&M University, Hazard Reduction and Recovery Center (HRRC);
Texas A&M University, Department of Landscape Architecture and Urban Planning (LAUP)
Scope of Project
Subject Terms:
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census data;
API;
NHGIS;
python;
google colaboratory;
google colab;
US Census API
Geographic Coverage:
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Block Groups in Galveston County, Texas
Time Period(s):
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2005 – 2009 (2009 5-year ACS)
Universe:
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For Median Household Income: All Households
For Race and Ethnicity: All Persons
For Race and Ethnicity: All Persons
Data Type(s):
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aggregate data;
census/enumeration data;
geographic information system (GIS) data;
images: photographs, drawings, graphical representations;
program source code
Methodology
Data Source:
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Steven Manson, Jonathan Schroeder, David Van Riper, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 14.0 [Database]. Minneapolis, MN: IPUMS. 2019. http://doi.org/10.18128/D050.V14.0
U.S. Census Bureau (2009). 2005-2009 American Community Survey 5-year Estimates. Retrieved from https://api.ipums.org.
U.S. Census Bureau (2009). 2005-2009 American Community Survey 5-year Estimates. Retrieved from https://api.ipums.org.
Unit(s) of Observation:
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Block Group,
County
Geographic Unit:
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Block Group
Related Publications
Published Versions
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This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.