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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'M49 Code'}) and 13 missing columns ({'Flag', 'Indicator Code', 'Year Code', 'Note', 'Institution Code', 'Area Code (M49)', 'Cost Category Code', 'Year', 'Unit', 'Value', 'Indicator', 'Cost Category', 'Institution'}).

This happened while the csv dataset builder was generating data using

zip://ASTI_Expenditures_E_AreaCodes.csv::hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Expenditures_E_All_Data_(Normalized).zip, ['hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Expenditures_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Researchers_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Climate_change_Emissions_indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/CommodityBalances_(non-food)_(-2013_old_methodology)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/CommodityBalances_(non-food)_(2010-)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ConsumerPriceIndices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Cost_Affordability_Healthy_Diet_(CoAHD)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Deflators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Development_Assistance_to_Agriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Agriculture_Energy_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Drained_Organic_Soils_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Land_Use_Fires_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Land_Use_Forests_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Pre_Post_Production_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Totals_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_crops_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Employment_Indicators_Agriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Employment_Indicators_Rural_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Bioenergy_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Cropland_nutrient_budget_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Emissions_intensities_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LandCover_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LivestockManure_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LivestockPatterns_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Temperature_change_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Exchange_rate_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Fertilizers_DetailedTradeMatrix_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/FoodBalanceSheetsHistoric_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/FoodBalanceSheets_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Food_Security_Data_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_Pulp_Paper_Survey_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_Trade_Flows_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Household_Consumption_and_Expenditure_Surveys_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Individual_Quantitative_Dietary_Data_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersArchive_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersNutrient_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersProduct_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_LandUse_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_Pesticides_Trade_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_Pesticides_Use_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_CapitalStock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_CreditAgriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_ForeignDirectInvestment_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_GovernmentExpenditure_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_MachineryArchive_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_Machinery_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Macro-Statistics_Key_Indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Minimum_Dietary_Diversity_for_Women_(MDD-W)_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Population_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Prices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Production_Crops_Livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Production_Indices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Rural_Livelihoods_Indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/SDG_BulkDownloads_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/SUA_Crops_Livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Suite_of_gender_indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Supply_Utilization_Accounts_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_CropsLivestockIndicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_CropsLivestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_DetailedTradeMatrix_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_Indices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Value_of_Production_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Value_shares_industry_primary_factors_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/World_Census_Agriculture_E_All_Data_(Normalized).zip']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Area Code: int64
              M49 Code: string
              Area: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 618
              to
              {'Area Code': Value('int64'), 'Area Code (M49)': Value('string'), 'Area': Value('string'), 'Indicator Code': Value('int64'), 'Indicator': Value('string'), 'Cost Category Code': Value('int64'), 'Cost Category': Value('string'), 'Institution Code': Value('int64'), 'Institution': Value('string'), 'Year Code': Value('int64'), 'Year': Value('int64'), 'Unit': Value('string'), 'Value': Value('float64'), 'Flag': Value('string'), 'Note': Value('float64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'M49 Code'}) and 13 missing columns ({'Flag', 'Indicator Code', 'Year Code', 'Note', 'Institution Code', 'Area Code (M49)', 'Cost Category Code', 'Year', 'Unit', 'Value', 'Indicator', 'Cost Category', 'Institution'}).
              
              This happened while the csv dataset builder was generating data using
              
              zip://ASTI_Expenditures_E_AreaCodes.csv::hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Expenditures_E_All_Data_(Normalized).zip, ['hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Expenditures_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ASTI_Researchers_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Climate_change_Emissions_indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/CommodityBalances_(non-food)_(-2013_old_methodology)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/CommodityBalances_(non-food)_(2010-)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/ConsumerPriceIndices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Cost_Affordability_Healthy_Diet_(CoAHD)_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Deflators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Development_Assistance_to_Agriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Agriculture_Energy_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Drained_Organic_Soils_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Land_Use_Fires_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Land_Use_Forests_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Pre_Post_Production_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_Totals_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_crops_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Emissions_livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Employment_Indicators_Agriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Employment_Indicators_Rural_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Bioenergy_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Cropland_nutrient_budget_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Emissions_intensities_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LandCover_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LivestockManure_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_LivestockPatterns_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Environment_Temperature_change_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Exchange_rate_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Fertilizers_DetailedTradeMatrix_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/FoodBalanceSheetsHistoric_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/FoodBalanceSheets_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Food_Security_Data_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_Pulp_Paper_Survey_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Forestry_Trade_Flows_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Household_Consumption_and_Expenditure_Surveys_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Individual_Quantitative_Dietary_Data_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersArchive_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersNutrient_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_FertilizersProduct_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_LandUse_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_Pesticides_Trade_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Inputs_Pesticides_Use_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_CapitalStock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_CreditAgriculture_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_ForeignDirectInvestment_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_GovernmentExpenditure_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_MachineryArchive_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Investment_Machinery_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Macro-Statistics_Key_Indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Minimum_Dietary_Diversity_for_Women_(MDD-W)_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Population_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Prices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Production_Crops_Livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Production_Indices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Rural_Livelihoods_Indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/SDG_BulkDownloads_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/SUA_Crops_Livestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Suite_of_gender_indicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Supply_Utilization_Accounts_Food_and_Diet_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_CropsLivestockIndicators_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_CropsLivestock_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_DetailedTradeMatrix_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Trade_Indices_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Value_of_Production_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/Value_shares_industry_primary_factors_E_All_Data_(Normalized).zip', 'hf://datasets/yuiseki/faostat@1908be260630c5b5156a1a694aaa6570b4086318/raw/2026-10-04/World_Census_Agriculture_E_All_Data_(Normalized).zip']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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Area Code
int64
Area Code (M49)
string
Area
string
Indicator Code
int64
Indicator
string
Cost Category Code
int64
Cost Category
string
Institution Code
int64
Institution
string
Year Code
int64
Year
int64
Unit
string
Value
float64
Flag
string
Note
null
3
'008
Albania
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million SLC
1,011.288
A
null
3
'008
Albania
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million SLC
806.1819
A
null
3
'008
Albania
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million USD
6.4002
A
null
3
'008
Albania
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million USD
17.6356
A
null
3
'008
Albania
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
%
0.26
A
null
4
'012
Algeria
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
1,715.7112
X
null
4
'012
Algeria
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
1,838.7656
X
null
4
'012
Algeria
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
2,527.0857
X
null
4
'012
Algeria
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
2,952.1366
X
null
4
'012
Algeria
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
2,434.5482
X
null
4
'012
Algeria
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
2,257.8995
X
null
4
'012
Algeria
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
2,654.3082
X
null
4
'012
Algeria
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
2,871.0068
X
null
4
'012
Algeria
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million USD
24.1783
X
null
4
'012
Algeria
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million USD
22.4239
X
null
4
'012
Algeria
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million USD
26.3608
X
null
4
'012
Algeria
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million USD
28.5129
X
null
4
'012
Algeria
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million USD
71.256
X
null
4
'012
Algeria
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million USD
66.0857
X
null
4
'012
Algeria
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million USD
77.688
X
null
4
'012
Algeria
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million USD
84.0305
X
null
4
'012
Algeria
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
%
0.2
X
null
4
'012
Algeria
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
%
0.18
X
null
4
'012
Algeria
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
%
0.22
X
null
4
'012
Algeria
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
%
0.21
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million SLC
2.3913
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million SLC
2.1787
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
1.9887
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
1.8655
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
2.1688
X
null
8
'028
Antigua and Barbuda
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
1.8328
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million SLC
2.7283
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million SLC
2.3733
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
2.1426
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
1.978
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
2.2739
X
null
8
'028
Antigua and Barbuda
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
1.8738
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million USD
1.0105
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million USD
0.879
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million USD
0.7935
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million USD
0.7326
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million USD
0.8422
X
null
8
'028
Antigua and Barbuda
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million USD
0.694
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million USD
1.319
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million USD
1.1473
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million USD
1.0358
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million USD
0.9562
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million USD
1.0992
X
null
8
'028
Antigua and Barbuda
8,003
Total Expenditure in Agricultural R&D (US$ PPP, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million USD
0.9058
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
%
5.05
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
%
4.58
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
%
4.78
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
%
4.38
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
%
4.41
X
null
8
'028
Antigua and Barbuda
8,006
Expenditure in Agricultural R&D as Share of Agricultural Value Added (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
%
3.61
X
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,004
2,004
million SLC
395.8299
X
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,005
2,005
million SLC
457.6151
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,006
2,006
million SLC
618.4418
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million SLC
681.8966
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million SLC
864.9725
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
999.9296
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
1,173.2286
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
1,514.8424
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
1,943.0843
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,013
2,013
million SLC
2,487.175
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,014
2,014
million SLC
3,243.1696
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,015
2,015
million SLC
4,392.8919
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,016
2,016
million SLC
5,276.7471
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,017
2,017
million SLC
6,899.2504
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,018
2,018
million SLC
8,226.2528
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,019
2,019
million SLC
11,518.785
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,020
2,020
million SLC
16,407.0117
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,021
2,021
million SLC
26,346.0718
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,022
2,022
million SLC
48,836.0312
A
null
9
'032
Argentina
8,000
Total Expenditure in Agricultural R&D (Standard Local Currency)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million SLC
123,798.8905
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,004
2,004
million SLC
3,266.827
X
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,005
2,005
million SLC
3,423.5244
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,006
2,006
million SLC
4,067.7535
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million SLC
3,902.1449
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million SLC
4,018.631
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,009
2,009
million SLC
4,026.4619
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,010
2,010
million SLC
3,907.1147
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,011
2,011
million SLC
4,078.1115
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,012
2,012
million SLC
4,276.6526
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,013
2,013
million SLC
4,416.481
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,014
2,014
million SLC
4,105.2038
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,015
2,015
million SLC
4,392.8919
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,016
2,016
million SLC
3,739.208
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,017
2,017
million SLC
3,879.9195
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,018
2,018
million SLC
3,257.1035
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,019
2,019
million SLC
3,056.8929
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,020
2,020
million SLC
3,108.2599
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,021
2,021
million SLC
3,245.2001
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,022
2,022
million SLC
3,559.5503
A
null
9
'032
Argentina
8,001
Total Expenditure in Agricultural R&D (Standard Local Currency, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,023
2,023
million SLC
3,811.4967
A
null
9
'032
Argentina
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,004
2,004
million USD
353.8136
X
null
9
'032
Argentina
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,005
2,005
million USD
370.7847
A
null
9
'032
Argentina
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,006
2,006
million USD
440.558
A
null
9
'032
Argentina
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,007
2,007
million USD
422.6217
A
null
9
'032
Argentina
8,002
Total Expenditure in Agricultural R&D (US$, 2015 prices)
300
Total
200
Government, Higher Education and Private Non-profit
2,008
2,008
million USD
435.2378
A
null
End of preview.

faostat

The FAOSTAT bulk downloads of the Food and Agriculture Organization of the United Nations (FAO): 66 domain zips, as the bulk-download catalogue listed them on 2026-10-04 (production, trade, food balances, prices, land use, inputs, emissions, forestry, population and employment, investment, food security, SDG indicators and others). Each zip holds the domain's data as a long ("Normalized") CSV for all areas, plus its code lists (areas, items, elements, flags). The zips are exactly as FAO serves them; this dataset is a mirror, not a reformatting.

Source: https://www.fao.org/faostat/en/; catalogue https://bulks-faostat.fao.org/production/datasets_E.json (Last-Modified Fri, 02 Oct 2026 08:16:55 GMT).

The data follows upstream corrections

FAO overwrites the catalogue and the zips in place under the same names. This dataset therefore holds one run, the newest, and is replaced as a whole when it is fetched again; older runs are not kept here. The current run is raw/2026-10-04/; MANIFEST.json gives for each file its URL, size, sha256, Last-Modified, fetch time and the catalogue's own entry (domain code, name, DateUpdate, row count).

Layout

raw/2026-10-04/MANIFEST.json
raw/2026-10-04/datasets_E.json                    the catalogue, as received
raw/2026-10-04/<Domain>_E_All_Data_(Normalized).zip   66 files, 1.52 GB

The CSVs in each zip are as FAO writes them. Most are valid UTF-8; some are not (8 data files and 7 code lists on 2026-10-04), so open them with an explicit legacy encoding such as Latin-1 when UTF-8 fails. Columns are, for most domains, Area Code, Area Code (M49), Area, Item Code, Item, Element Code, Element, Year Code, Year, Unit, Value, Flag, Note.

Left out: domains that may not be under CC BY

FAO's licensing policy (https://openknowledge.fao.org/handle/20.500.14283/cd7464en) puts its statistical databases under CC BY 4.0 from 30 November 2019 on, and says databases published before that date are not under a Creative Commons licence unless marked so. Three discontinued series have a catalogue DateUpdate before that date, and nothing in the catalogue marks them. They are not published here (MANIFEST.json still lists them, with the reason):

  • Food_Aid_Shipments_WFP_E_All_Data_(Normalized).zip (FA, Discontinued archives and data series: Food Aid Shipments (WFP); last update 2016-12-22, 31,114 rows)
  • Indicators_from_Household_Surveys_E_All_Data_(Normalized).zip (HS, Discontinued archives and data series: Indicators from Household Surveys (gender, area, socioeconomics); last update 2014-07-31, 148,620 rows)
  • PricesArchive_E_All_Data_(Normalized).zip (PA, Discontinued archives and data series: Producer Prices (old series); last update 1991-12-31, 139,713 rows)

Licence

FAO statistical databases are licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode.en), complemented by the FAO Statistical Database Terms of Use (https://www.fao.org/contact-us/terms/db-terms-of-use/en/), which add terms of their own: no use in promoting a commercial enterprise or suggesting FAO endorsement, data of third parties may carry other conditions, and disputes go to UNCITRAL arbitration. Required citation format:

FAO. [year of last update]. [Name of database: Name of dataset]. [Accessed on DD Month YYYY]. [URL] Licence: CC-BY-4.0.

Collection code: https://github.com/yuiseki/faostat (MIT).

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