Revised 3 November 2026 · v1.0.0 · what changed

Code: github.com/herrrickshaw/india-trade-data-analysis

Watch the walkthrough

Watch on YouTube: youtu.be/ZvdlH4DdWtA

Why it is useful

• Who benefits: students, journalists and policy analysts who need a sourced, dated view of India's trade position without stitching together four agencies' sites.
• What it replaces: manual downloads from TRADESTAT, RBI and MoSPI. The repo ships the extracts as JSON plus ready-made charts.
• Evidence from our read: the five-year synthesis file shows imports up 26.58% against exports up 4.68% over FY2021-22 to FY2025-26.
• It cross-checks itself: a validation file compares TRADESTAT totals with the Commerce Ministry TIA portal and notes a roughly 2% gap in exports.
• Everything is in US$ million, which makes cross-source comparison simple.

What it is for

The repo records what the data show: CPI and WPI by state, GDP growth with revisions, forex reserves, the rupee, the goods and services balance, and imports and exports by HS chapter, from FY2018-19 to FY2025-26. A five-year synthesis re-cuts all threads to one window and a sample FY2025-26 report standardises units.

It is the data half of a split. The prescriptive recommendations live in india-trade-sector-policy-recommendations. This is economic analysis, not investment or legal advice.

Who it is for

• Students and researchers studying India's external sector
• Journalists verifying a trade or reserves figure against a dated source
• Analysts who want JSON extracts for their own notebooks

What you need

Get the code and an AI assistant

You do not have to be a programmer. Get the repository, give it to an AI assistant, and ask in plain language. Any of these routes works:

git clone https://github.com/herrrickshaw/india-trade-data-analysis.git
cd india-trade-data-analysis
claude      # or: gemini

Install

1. Get the code

   git clone https://github.com/herrrickshaw/india-trade-data-analysis.git
   cd india-trade-data-analysis

2. Or just open the live site

   https://herrrickshaw.github.io/india-trade-data-analysis/

Quick start: commands and what you should see

Print the five-year import and export totals

python3 -c "import json;d=json.load(open('data/five_year_trade_currency_synthesis_2026-07-18.json'))['trade_totals_usd_million'];print(d['years']);print(d['export']);print(d['import']);print(d['export_growth_5yr_pct'],d['import_growth_5yr_pct'])"

Five fiscal years of exports and imports in US$ million, then 4.68 and 26.58 percent growth.

Sample outputs

Real output from a run on the date shown in the sources line; trimmed to fit.

Five-year trade totals (US$ million)

data/five_year_trade_currency_synthesis_2026-07-18.json
years:   2021-22   2022-23   2023-24   2024-25   2025-26
export:  422004.4  451070.0  437072.1  437704.5  441745.9
import:  613052.1  715968.9  678214.8  721200.3  776013.7
export growth 5yr: 4.68%   import growth 5yr: 26.58%

Read from the committed file; FY2025-26 is provisional.

Goods deficit versus services surplus (US$ billion)

goods_services_balance_usd_billion
years:         2021-22  2022-23  2023-24  2024-25
goods_balance: -191.0   -264.9   -241.1   -283.5
services_net:   107.6    143.6    162.8    188.9
overall:        -83.5   -121.3    -78.3    -94.6

The file states the services surplus covers about 87.9% of the extra goods gap.

Top import chapters by value, FY2025-26 (US$ million, growth since FY2018-19)

hsn_historical_trends_2018-19_to_2025-26.json
HS27 Mineral fuels & oils        203,415.4   +21.2%
HS71 Pearls, gems & jewellery    109,430.2   +69.1%
HS85 Electrical machinery        104,852.7  +101.5%
HS84 Machinery                    74,019.5   +68.8%
HS29 Organic chemicals            25,410.7   +13.5%
HS39 Plastics                     22,234.5   +45.8%

The top 12 import chapters together are 81.5% of imports.

Ways to use it

Sample prompts for your AI assistant

Copy, paste and edit the parts in [brackets].

• Read README.md in this repository and explain in plain English what it contains and how the files relate to each other.
• Open the main data file and summarise the three most important findings with the exact numbers and the file they come from.
• List every caveat or data-quality warning the author documents, and tell me which ones affect the figures I plan to quote.
• Show me how to load one of the JSON files in Python (or Excel) and make a simple table of the top 10 rows by value.
• Explain how I would update this analysis with newer official data, and what I would need to re-check by hand.

Limits and honest caveats

Sources: Repo herrrickshaw/india-trade-data-analysis (README; data/five_year_trade_currency_synthesis_2026-07-18.json, trade_data_cross_validation_2026-07-18.json, hsn_historical_trends_2018-19_to_2025-26.json); underlying MoSPI, RBI and DGCI&S/TRADESTAT data as recorded by the repo. Files read 19 October 2026; nothing re-fetched.

About this article: Researched, written and edited by Umashankar Triplicane Dwarakanathan, with AI research assistance; every figure is meant to trace to the primary source cited. See the Editorial Policy for how sourcing, AI use and corrections work.