This dataset represents a subset of agricultural crop survey records collected during the 2018–2019 season, including crop types, cultivated land extent, and geospatial coordinates.
| Name | Type | Nullable | Description |
|---|---|---|---|
| CropSurveyDate | date | No | |
| Crop_Extent | string | No | |
| Cropname | categorical | Yes | |
| District_Name | categorical | No | |
| District_code | integer | No |
The dataset contains 10,721 crop survey entries collected at the field level. Each record includes crop type, land extent (in a composite land unit format), and precise geographic coordinates (latitude and longitude). Administrative hierarchy is captured through district, taluk, hobli, and village identifiers and names. Temporal attributes include survey date, agricultural season, and partial time segmentation via month and week fields. The dataset appears to be a regional subset of a larger agricultural monitoring system and reflects structured data collection likely used for crop tracking and planning.
The dataset maintains strong consistency in administrative and geographic fields with no missing values. However, Cropname contains some missing values (~6%). Columns such as Month and Weekname are sparsely populated (~32% filled), limiting temporal granularity. Image_url is completely empty, indicating missing auxiliary data. Crop_Extent is stored in a non-standard string format requiring preprocessing for numeric analysis.
Agricultural production analysis, crop distribution mapping, regional planning, yield estimation modeling, GIS-based analytics, government policy design, and precision farming applications.
Crop extent is not directly numeric and requires parsing. Missing values in Cropname, Month, and Weekname reduce analytical completeness. Absence of image data limits validation through visual inspection. Dataset is limited to a specific geographic region and time period.
Data was likely collected through on-ground agricultural surveys using digital tools capturing crop details, GPS coordinates, and administrative classifications. Survey IDs and structured codes indicate integration with a centralized agricultural data collection system.
License: GODL-India — This dataset is licensed for use by the purchasing entity. Refer to the specific license terms for permitted use.
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