Interactive map
Interactive map for U.S. Cotton Production by County. Use the map controls to pan and zoom.
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U.S. Cotton Production by County
Geography: United States counties
Dataset last updated:
U.S. Cotton Production by County
This interactive map presents annual county-level cotton estimates published by the U.S. Department of Agriculture National Agricultural Statistics Service (USDA NASS). Coverage begins in 1919 and extends through the latest year shown in the Year selector.
The dataset reports upland cotton and Pima cotton as separate outputs. Values for the two cotton types are not combined into a single total-cotton series.
Data were obtained from the USDA NASS Quick Stats database under the Survey program. These are annual agricultural survey estimates rather than five-year Census of Agriculture data.
Available measures
Each cotton type may include the following measures:
- Harvested Area - acres harvested.
- Planted Area - acres planted, when published.
- Production - production measured in 480-pound bales.
- Yield - pounds produced per harvested acre.
Historical availability
- Upland harvested area, production, and yield are available throughout the included period beginning in 1919.
- Upland planted area begins in 1928.
- Pima measures begin in 1935.
- The source contains no county-level Pima values for 2019.
The available cotton type and measures therefore vary by year. Select a year and measure to see the published geographic coverage for that combination.
Geographic coverage
The map covers United States counties, but data are displayed only for counties with a published USDA NASS cotton estimate. Upland cotton is reported across a wider geographic area, while Pima cotton is concentrated in a relatively small number of counties. Reporting coverage varies over time.
Interpreting the map
- An unshaded county generally indicates that no value was published and should not automatically be interpreted as zero.
- Counties view colors current county polygons using the selected published value.
- Surface view interpolates county values to illustrate broad regional patterns. It should not be interpreted as a measured value between reporting counties.
- Survey methods, reporting coverage, and publication practices may change across a long historical series.
- Historical records may use county names or boundaries that no longer exist. Retired historical geographies may not display on the current county map.
Data source and preparation
Source data were downloaded from the USDA NASS Quick Stats database and restructured for use in CU-CAT Maps. County identifiers were standardized using FIPS codes where supported. Missing values were left blank and were not replaced with zeros.
Platform and data responsibility
CU-CAT Maps is developed and hosted by the Clemson University Center for Agricultural Technology (CU-CAT), in partnership with Clemson Cooperative Extension Service.
CU-CAT provides the mapping platform. The hosted dataset and dataset-specific content presented on this page are maintained by Kendall Kirk. CU-CAT's role in creating, verifying, or maintaining hosted data varies by page. For questions about the data presented here, contact Kendall Kirk.
CU-CAT Maps and its maps, reports, and results are provided as-is for informational purposes. Accuracy and completeness are not guaranteed. Users are responsible for evaluating the source data and outputs and assume the risks arising from their use. See the Terms of Use.
Have feedback about CU-CAT Maps, want to discuss whether a dataset may be a good fit for the platform, or have a dataset or topic you would like to see mapped? Email CU-CAT. Hosting and support depend on alignment with CU-CAT's mission, project scope, and available capacity.
© 2025-2026 Clemson University Center for Agricultural Technology (CU-CAT) and Clemson Cooperative Extension Service
Use the controls above the map to choose what to display, how to display it, and what to save or report.
Start with the data
- Choose a dataset. Most pages open with a hosted dataset. Pages with an Upload data control also let you select an Excel or CSV file for your current browser session.
- Choose a sheet. The Sheet selector appears when the dataset contains more than one available worksheet.
- Choose a variable. The Variable selector lists the columns that can be mapped. Changing the variable updates the map, legend, popups, and reports.
Choose a map view
Regions
Regions colors each mapped area according to its value or category. Use it for exact regional comparisons, popups, labels, and reporting.
Surface
Surface estimates a continuous pattern from values associated with the mapped regions. Use it to explore broad spatial trends rather than to infer exact values between regions.
Start simply: choose the view and variable first. Open Advanced only when you need to adjust classification, colors, opacity, interpolation, or other display settings.
Explore the map
- Pan and zoom as you would on a standard online map.
- In Regions view, select a region to inspect its popup. The popup may also offer a report for that region.
- In Surface view, turn on points when you need to see the observations used to create the surface.
- Use the legend to interpret colors, ranges, units, totals, averages, and areas without data.
Reports and exports
- Attribute report: compares regions for the selected variable. Sort a report table before exporting when order matters.
- Region report: available from a region popup in Regions view and compares variables for that region.
- Copy map: copies the map image when the browser supports image copying.
- Download map: saves the map as a PNG image.
- Share: shares or copies the page link. It does not currently preserve the selected map settings.
Exported map images include the data layers and legend but omit third-party basemap tiles.
Interpret with care
- Check the units and source information supplied in the About tab.
- Do not assume a missing value means zero unless the dataset supports that interpretation.
- Surface maps are generalized visualizations. Classification, smoothing, clipping, and interpolation settings can change their appearance.
- When duplicate rows are present, averaging and summing answer different questions. Use the method appropriate for the data.