Data Dictionary

ID
id
Type
int4
Label
index

ID
date
Type
date
Label
Date

ID
country_name
Type
text
Label
Country Name

ID
alpha_3_code
Type
text
Label
ISO Alpha 3 Code

ID
country_code
Type
text
Label
Country Code

ID
region
Type
text
Label
Region Name

ID
region_code
Type
text
Label
Region Code

ID
sub_region
Type
text
Label
Sub-Region Name

ID
sub_region_code
Type
text
Label
Sub-Region Code

ID
hs_code
Type
text
Label
Harmonized System Code

ID
commodity
Type
text
Label
Commodity Name

ID
unit
Type
text
Label
Unit of Quantity

ID
value_qt
Type
numeric
Label
Quantity of commodity

ID
value_rs
Type
numeric
Label
Value of commodity quantity in INR

ID
value_dl
Type
numeric
Label
Value of commodity quantity in US Dollars

Additional Information

Field Value
Data last updated May 8, 2025
Metadata last updated May 8, 2025
Created October 23, 2023
Format CSV
License Open Data Commons Attribution License
Additional infonan
Data extraction pagehttps://tradestat.commerce.gov.in/meidb/cntcomq.asp?ie=i
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 updated2024-10-01
Data retreival date2025-05-08
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
Size11.8 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 covered2017-2024
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/cntcomq.asp?ie=i
Data Retreival Date 2025-05-08
Data Last Updated 2024-10-01
Sku mci-tradestat_import_lfy-cn-mn-oce
Dataset Frequency Monthly
Years Covered 2017-2024
No of States/UT(s)
No of Districts
No of Tehsils/blocks
No of Gram Panchayats
Additional 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