Food Access Python Library
From the CORGIS Dataset Project
By Ryan Whitcomb, Joung Min Choi, Bo Guan Version 3.0.0, created 9/14/2021 Tags: counties, states, food, access, availability, supermarket, rural, urban, population, vehicles
Overview
From the United States Department of Agriculture’s Economic Research Service, the dataset contains information about US county’s ability to access supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food. Most measures of how individuals and neighborhoods are able to access food are based on the following indicators:
- Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area.
- Individual-level resources that may affect accessibility, such as family income or vehicle availability.
- Neighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.
https://www.ers.usda.gov/data-products/food-access-research-atlas/download-the-data/
Explore Structure
Each row represents *Information about each state’s ability to access food *.
Explore food access data
Index Type Example Value
0
dict
{
1 dict (same structure)
2 dict (same structure)
... ... ...
Key Type Example Value Description
"County"
str
"Autauga County"
County name
"Population"
int
54571
Population count from 2010 census
"State"
str
"Alabama"
State name
"Housing Data"
dict
{
"Vehicle Access"
dict
{
"Low Access Numbers"
dict
{
Key Type Example Value Description
"Residing in Group Quarters"
float
455.0
Count of tract population residing in group quarters
"Total Housing Units"
int
20221
Occupied housing unit count from 2010 census
Key Type Example Value Description
"1 Mile"
float
834.0
Housing units without vehicle count beyond 1 mile from supermarket
"1/2 Mile"
float
1045.0
Housing units without vehicle count beyond 1/2 mile from supermarket
"10 Miles"
float
222.0
Housing units without vehicle count beyond 10 miles from supermarket
"20 Miles"
float
0.0
Housing units without vehicle count beyond 20 miles from supermarket
Key Type Example Value Description
"Children"
dict
{
"Low Income People"
dict
{
"People"
dict
{
"Seniors"
dict
{
Key Type Example Value Description
"1 Mile"
float
9973.0
Kids population count beyond 1 mile from supermarket
"1/2 Mile"
float
13281.0
Kids population count beyond 1/2 mile from supermarket
"10 Miles"
float
1199.0
Kids population count beyond 10 miles from supermarket
"20 Miles"
float
0.0
Kids population count beyond 20 miles from supermarket
Key Type Example Value Description
"1 Mile"
float
12067.0
Low income population count beyond 1 mile from supermarket
"1/2 Mile"
float
15518.0
Low income population count beyond 1/2 mile from supermarket
"10 Miles"
float
2307.0
Low income population count beyond 10 miles from supermarket
"20 Miles"
float
0.0
Low income population count beyond 20 miles from supermarket
Key Type Example Value Description
"1 Mile"
float
37424.0
Population count beyond 1 mile from supermarket
"1/2 Mile"
float
49497.0
Population count beyond 1/2 mile from supermarket
"10 Miles"
float
5119.0
Population count beyond 10 miles from supermarket
"20 Miles"
float
0.0
Population count beyond 20 miles from supermarket
Key Type Example Value Description
"1 Mile"
float
4393.0
Seniors population count beyond 1 mile from supermarket
"1/2 Mile"
float
5935.0
Seniors population count beyond 1/2 mile from supermarket
"10 Miles"
float
707.0
Seniors population count beyond 10 miles from supermarket
"20 Miles"
float
0.0
Seniors population count beyond 20 miles from supermarket
Downloads
Download all of the following files.
food_access.py food_access.data
Usage
import food_access
record = food_access . get_record ()
Documentation
get_record() Returns a list of dictionaries representing record.
