Name: Agricultural Production
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Agricultural Production

This dataset offers a detailed examination of agricultural production practices and harvest data for various crops in Northern Valley, Colbert County, Alabama, for the year 2002. The data is sourced from the Census, providing a reliable and structured overview of crop cultivation, harvest areas, and specific production practices. The dataset includes information on different sectors, groups, commodities, and classes of crops, along with details on production and utilization practices.

Key Features

Crop Categories: The dataset covers a wide range of crop categories, including vegetables (e.g., snap beans) and field crops (e.g., cotton).
Production Practices: Detailed information on production practices such as irrigation and utilization practices is provided for each crop.
Harvest Areas: The dataset includes the area harvested for each crop in acres, offering insights into the scale of agricultural operations.
Geographical Details: Specific details about the location, including county, state, and regional descriptors, are included to provide context for the agricultural data.
Temporal Information: The dataset is time-stamped with the year of data collection (2002) and the load time, ensuring data accuracy and relevance.

Potential Uses

Agricultural Planning: Assist in agricultural planning and resource allocation by understanding the scale and practices of crop production in specific regions.
Production Efficiency Analysis: Analyze the efficiency of different production practices, such as irrigation, in enhancing crop yield.
Regional Crop Comparison: Compare the production and harvest areas of different crops within the same region to identify dominant agricultural activities.
Historical Agricultural Trends: Track historical trends in agricultural production practices and harvest areas to inform future agricultural policies and strategies.
Environmental Impact Assessment: Evaluate the environmental impact of agricultural practices, such as irrigation, on local ecosystems.

Tables

Agricultural Production Animas Products 2024

@kaggle.noeyislearning_agricultural_production.agricultural_production_animas_products_2024

279.2 MB
10,089,429 rows
39 columns

CREATE TABLE agricultural_production_animas_products_2024 (
  "source_desc" VARCHAR,
  "sector_desc" VARCHAR,
  "group_desc" VARCHAR,
  "commodity_desc" VARCHAR,
  "class_desc" VARCHAR,
  "prodn_practice_desc" VARCHAR,
  "util_practice_desc" VARCHAR,
  "statisticcat_desc" VARCHAR,
  "unit_desc" VARCHAR,
  "short_desc" VARCHAR,
  "domain_desc" VARCHAR,
  "domaincat_desc" VARCHAR,
  "agg_level_desc" VARCHAR,
  "state_ansi" DOUBLE,
  "state_fips_code" BIGINT,
  "state_alpha" VARCHAR,
  "state_name" VARCHAR,
  "asd_code" DOUBLE,
  "asd_desc" VARCHAR,
  "county_ansi" DOUBLE,
  "county_code" DOUBLE,
  "county_name" VARCHAR,
  "region_desc" VARCHAR,
  "zip_5" DOUBLE,
  "watershed_code" BIGINT,
  "watershed_desc" VARCHAR,
  "congr_district_code" DOUBLE,
  "country_code" BIGINT,
  "country_name" VARCHAR,
  "location_desc" VARCHAR,
  "year" BIGINT,
  "freq_desc" VARCHAR,
  "begin_code" BIGINT,
  "end_code" BIGINT,
  "reference_period_desc" VARCHAR,
  "week_ending" TIMESTAMP,
  "load_time" TIMESTAMP,
  "value" VARCHAR,
  "cv" VARCHAR  -- CV %
);

Agricultural Production Census 2002

@kaggle.noeyislearning_agricultural_production.agricultural_production_census_2002

16.13 MB
3,193,989 rows
39 columns

CREATE TABLE agricultural_production_census_2002 (
  "source_desc" VARCHAR,
  "sector_desc" VARCHAR,
  "group_desc" VARCHAR,
  "commodity_desc" VARCHAR,
  "class_desc" VARCHAR,
  "prodn_practice_desc" VARCHAR,
  "util_practice_desc" VARCHAR,
  "statisticcat_desc" VARCHAR,
  "unit_desc" VARCHAR,
  "short_desc" VARCHAR,
  "domain_desc" VARCHAR,
  "domaincat_desc" VARCHAR,
  "agg_level_desc" VARCHAR,
  "state_ansi" DOUBLE,
  "state_fips_code" BIGINT,
  "state_alpha" VARCHAR,
  "state_name" VARCHAR,
  "asd_code" DOUBLE,
  "asd_desc" VARCHAR,
  "county_ansi" DOUBLE,
  "county_code" DOUBLE,
  "county_name" VARCHAR,
  "region_desc" VARCHAR,
  "zip_5" VARCHAR,
  "watershed_code" BIGINT,
  "watershed_desc" VARCHAR,
  "congr_district_code" VARCHAR,
  "country_code" BIGINT,
  "country_name" VARCHAR,
  "location_desc" VARCHAR,
  "year" BIGINT,
  "freq_desc" VARCHAR,
  "begin_code" BIGINT,
  "end_code" BIGINT,
  "reference_period_desc" VARCHAR,
  "week_ending" VARCHAR,
  "load_time" TIMESTAMP,
  "value" VARCHAR,
  "cv" VARCHAR  -- CV %
);

Agricultural Production Census 2007

@kaggle.noeyislearning_agricultural_production.agricultural_production_census_2007

27.54 MB
5,617,531 rows
39 columns

CREATE TABLE agricultural_production_census_2007 (
  "source_desc" VARCHAR,
  "sector_desc" VARCHAR,
  "group_desc" VARCHAR,
  "commodity_desc" VARCHAR,
  "class_desc" VARCHAR,
  "prodn_practice_desc" VARCHAR,
  "util_practice_desc" VARCHAR,
  "statisticcat_desc" VARCHAR,
  "unit_desc" VARCHAR,
  "short_desc" VARCHAR,
  "domain_desc" VARCHAR,
  "domaincat_desc" VARCHAR,
  "agg_level_desc" VARCHAR,
  "state_ansi" DOUBLE,
  "state_fips_code" BIGINT,
  "state_alpha" VARCHAR,
  "state_name" VARCHAR,
  "asd_code" DOUBLE,
  "asd_desc" VARCHAR,
  "county_ansi" DOUBLE,
  "county_code" DOUBLE,
  "county_name" VARCHAR,
  "region_desc" VARCHAR,
  "zip_5" DOUBLE,
  "watershed_code" BIGINT,
  "watershed_desc" VARCHAR,
  "congr_district_code" VARCHAR,
  "country_code" BIGINT,
  "country_name" VARCHAR,
  "location_desc" VARCHAR,
  "year" BIGINT,
  "freq_desc" VARCHAR,
  "begin_code" BIGINT,
  "end_code" BIGINT,
  "reference_period_desc" VARCHAR,
  "week_ending" VARCHAR,
  "load_time" TIMESTAMP,
  "value" VARCHAR,
  "cv" VARCHAR  -- CV %
);