Data Dictionary

ID
id
Typ
int4
Etikett
index

ID
date
Typ
date
Etikett
Date

ID
country_name
Typ
text
Etikett
Country Name

ID
alpha_3_code
Typ
text
Etikett
ISO Alpha 3 Code

ID
country_code
Typ
text
Etikett
Country Code

ID
region
Typ
text
Etikett
Region Name

ID
region_code
Typ
text
Etikett
Region Code

ID
sub_region
Typ
text
Etikett
Sub-Region Name

ID
sub_region_code
Typ
text
Etikett
Sub-Region Code

ID
hs_code
Typ
text
Etikett
Harmonized System Code

ID
commodity
Typ
text
Etikett
Commodity Name

ID
unit
Typ
text
Etikett
Unit of Quantity

ID
value_qt
Typ
numeric
Etikett
Quantity of commodity

ID
value_rs
Typ
numeric
Etikett
Value of commodity quantity in INR

ID
value_dl
Typ
numeric
Etikett
Value of commodity quantity in US Dollars

Mer information

Fält Värde
Data senast uppdaterad 11 juni 2025
Metadata senast uppdaterad 11 juni 2025
Skapad 23 oktober 2023
Format CSV
Licens Open Data Commons Attribution License
Additional infonan
Data extraction pagehttps://tradestat.commerce.gov.in/meidb/country_wise_all_commodities_import
Data insightsData Insights that can be drawn:Trade Volume Analysis: Determine which Oceanic countries are the top trade partners in terms of volume and value.Commodity Classification: Understand the primary commodities imported from the Oceanic region.Trade Value Comparison: Compare the trade value in USD and INR to deduce exchange rate dynamics and their implications.Trade Trends Over Time: By analyzing the date column, temporal trends can be identified, aiding in understanding seasonal variations or changes in trade patterns over the years.Weight to Value Ratio: By comparing the "dollars_millions" and "quantity_thousands" columns, one can determine the commodities that bring in the highest value per KG.
Data last updated2025-06-06 00:00:00
Data retreival date2025-06-06 00:00:00
Datastore activeTrue
FrequencyMonthly
GranularityCountry
Has viewsTrue
Ida0a660b5-8b2a-43aa-84bb-8f49bdb5c2e4
Idp readyTrue
Lgd mappingna
MethodologyThe data has been sourced from the official website of the Department of Commerce, Government of India, which provides a comprehensive trade database for various commodities. The dataset's methodology centers on the Harmonized System (HS code) - a globally standardized system for classifying traded products. This ensures a consistent and comparable framework for understanding and analyzing trade data.
Mimetypetext/csv
No indicators3
Package id0e64447e-7e57-4e17-ac2a-6b86944abfb2
Position4
Size14,3 MiB
Skumci-tradestat_import_lfy-cn-mn-oce
Stateactive
Tags['Trade Statistics', 'Oceanic Trade', 'Commodities', 'Harmonized System', 'Trade Value', 'Import Quantity', 'Currency Analysis']
Url typeupload
Years covered2017-2025
Methodology The data has been sourced from the official website of the Department of Commerce, Government of India, which provides a comprehensive trade database for various commodities. The dataset's methodology centers on the Harmonized System (HS code) - a globally standardized system for classifying traded products. This ensures a consistent and comparable framework for understanding and analyzing trade data.
Indicators
Similar Resources
Granularity Level Country
Data Extraction Page https://tradestat.commerce.gov.in/meidb/country_wise_all_commodities_import
Data Retreival Date 2025-06-06 00:00:00
Data Last Updated 2025-06-06 00:00:00
Sku mci-tradestat_import_lfy-cn-mn-oce
Dataset Frequency Monthly
Years Covered 2017-2025
No of States/UT(s)
No of Districts
No of Tehsils/blocks
No of Gram Panchayats
Mer information nan
Number of Indicators 3
Insights from the dataset Data Insights that can be drawn:Trade Volume Analysis: Determine which Oceanic countries are the top trade partners in terms of volume and value.Commodity Classification: Understand the primary commodities imported from the Oceanic region.Trade Value Comparison: Compare the trade value in USD and INR to deduce exchange rate dynamics and their implications.Trade Trends Over Time: By analyzing the date column, temporal trends can be identified, aiding in understanding seasonal variations or changes in trade patterns over the years.Weight to Value Ratio: By comparing the "dollars_millions" and "quantity_thousands" columns, one can determine the commodities that bring in the highest value per KG.
IDP Ready Yes
LGD Mapping Not Applicable
Mapping Status %
Geo Columns