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Historical U.S. Farm Commodity Trade Data
Data Science and Analytics
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About
Monthly and historical records of United States agricultural trade capture the total value and trade balance of essential commodities. These metrics include year-to-date and current month exports and imports, highlighting performance across top markets for wheat, corn, soybeans, and cotton. The data facilitates a deep understanding of market trends for fruits and vegetables and provides a clear picture of the trade balance within the global agricultural sector. By tracking these FATUS groups and HTS codes, the resource serves as a foundation for monitoring the economic health of the farming industry and its international outreach.
Columns
The dataset includes 9 columns based on the original structure:
- US agricultural: Categorises the type of trade activity, such as agricultural exports or imports.
- dollars: The monetary value associated with the specific trade records.
- years: The calendar year associated with the recorded trade figures.
- total: The aggregate value or volume for the specific trade category.
- fiscal year: The financial reporting period for the agricultural metrics.
- year: An additional time-based identifier for yearly aggregation.
- August: Specific monthly data point or key identifier within the trade cycle.
- keys: A field for unique identifiers or categorical keys, which may contain null values in this version.
Distribution
The material is provided as a CSV file titled
agricula.csv, which is approximately 2.29 kB in size. The dataset consists of 9 columns and contains 23 total values. It is important to note that certain fields, such as 'years' and 'keys', exhibit a high percentage of missing values, ranging from 52% to 100%. The expected update frequency is recorded as Never.Usage
This resource is ideal for performing detailed trend analysis on U.S. agricultural exports and imports. It can be utilised to create interactive charts and summaries regarding the outlook for agricultural trade. Analysts can leverage the data for SQL-based cleaning, statistical modelling in TensorFlow, and data visualisation tasks to track the trade balance over several years. It is particularly useful for assessing the volume of top export markets for major crops like soybeans and corn.
Coverage
The geographic scope is focused on the United States and its global trading partners. The data encompasses current and historical monthly and yearly records, with specific instances highlighting the years 2019 and 2022. It covers diverse commodity groups including wheat, cotton, fruits, and vegetables.
License
CC0: Public Domain
Who Can Use It
Market analysts and economists can use these metrics to forecast agricultural trade performance and study market shifts. Data scientists may employ the CSV for training machine learning models related to economic trends. Government officials and trade organisations can also utilise the data to monitor the trade balance and export volumes for major agricultural products. The material holds a maximum usability rating of 10.00.
Dataset Name Suggestions
- U.S. Agricultural Trade Metrics and Market Performance
- Monthly Agricultural Export and Import Trade Balance
- Historical U.S. Farm Commodity Trade Data
Attributes
Original Data Source: Historical U.S. Farm Commodity Trade Data
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