Interactive map
Interactive map for South Carolina Soybean Production. Use the map controls to pan and zoom.
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South Carolina Soybean Production
Geography: South Carolina counties
Dataset last updated:
This interactive map presents county-level South Carolina soybean statistics for every reporting year currently included, beginning in 1972. The dataset is intended to be updated as new annual data become available. The year selector shows all reporting years currently included.
Information included
Each included year provides soybean harvested area, planted area, production measured in bushels, and yield measured in bushels per acre.
Selected reporting years provide additional information. Soybean operations, irrigated harvested area, and irrigated operations are included for 1997, 2002, 2007, 2012, 2017, and 2022. Operations with sales and soybean sales measured in dollars are included for 2007, 2012, 2017, and 2022.
Data source and preparation
These data were obtained from the USDA National Agricultural Statistics Service (NASS) Quick Stats database. NASS county estimates are derived from producer surveys, administrative information, and other statistical programs. Source records were cleaned and restructured into annual South Carolina county worksheets for mapping and report generation.
- Data are presented for South Carolina counties.
- Counties without a published value are shown as no data.
- Values suppressed, withheld, or otherwise unavailable in the source data remain unavailable and should not be interpreted as zero.
- Available variables and county coverage vary by reporting year.
- Recently completed reporting years may not appear until USDA NASS releases county-level estimates and the hosted dataset is updated.
- Users should consult USDA NASS documentation for official definitions, survey methods, revisions, and limitations.
Using the map
Counties view displays reported county values using classified colors. Surface view interpolates a continuous visualization from available county values to illustrate broad spatial patterns. Surface shading is not an official estimate for locations between county data points or for counties with unpublished values.
Users can select an available year and variable, adjust visualization settings, inspect county values, save map images, and generate PDF reports.
Intended use
This tool supports agricultural education, Extension programming, historical exploration, and data-informed discussion. Results should be interpreted in the context of source-data availability and NASS reporting practices.
Data source: USDA National Agricultural Statistics Service. Quick Stats database.
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.