Indian Bureau of Mines statistics: Indian Minerals Yearbook & mineral production

One national statistical agency, three linked series, one job: India's official mineral numbers. Indian Bureau of Mines statistics is the Government of India's mineral statistics estate, delivered here as typed rows instead of multi-hundred-page annual volumes. The Indian Minerals Yearbook is the flagship annual - the 2024 edition is its 63rd, carrying data year 2023-24 - organised into General Reviews (production, prices, foreign trade and state reviews), 19 Metals & Alloys reviews including gold, silver, platinum and palladium, and 26 alphabetical Mineral Reviews.

Each metal review is itself a small statistical library: reserve and resource tables on the UNFC system by state, principal producers, ore treated and grade, production in kilograms with rupee values by state, district and sector, bullion output, world reserves and mine production for context, and import/export tables. Around the yearbook sit the monthly Statistics of Mineral Production - month-wise quantity and value tables per mineral including gold ore, gold total/primary/by-product and silver - and the Average Sale Price series, the state-wise price tables required under MCDR 2017.

Scale, concretely: ten yearbook editions, roughly twelve monthly production issues a year plus corrigenda, and about eight average-sale-price issues per monthly cycle. Within Datadory's catalog of 1,744 datasets across 159 viable industries, this record scores 8/10 for quality, with field definitions verified.

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Real cells from the archive, shown flat exactly as their fields arrive:

# One real record, flat, exactly as the fields arrive
table             : IMYB 2024 Table 5 - Production of Gold by State
state             : India
year              : 2023-24 (P)
quantity_kg       : 1603
value_rs_000      : 9670820

# The same shape one level down, at state resolution
table             : IMYB 2024 Table 3 - Production of Gold Ore by State
state             : Karnataka
ore_produced_tonnes : 716486
avg_grade_g_per_t : 2.52
prior_year_ore_tonnes : 593677

# Monthly cadence from the production-statistics layer
table             : MSMP May 2026 Table 3 - Mineral Production
mineral           : Gold (total)
unit              : Kg
may_2026_qty      : 130.679
may_2026_value_rs_000 : 1971111
apr_may_2026_qty  : 276.743

# The shape every other record repeats
state/district    : <Indian state, district, or All-India total>
mineral           : <one of the reviewed metals & alloys or minerals>
period            : <fiscal year for the yearbook layer, calendar month otherwise>
quantity + value  : <figure> in <kg or tonnes> against <Rs '000>, provisional marker when flagged

Three things worth noticing in those rows. First, identity travels with the number: every figure names its printed table, its geography and its period, so a 1,603 kg figure is never just a number - it is primary gold, India, fiscal 2023-24, provisional, traceable to the exact table it was typeset in. Second, the layers stack honestly: one schema resolves at All-India, state and district level, which is how a single record carries both the national total and the Karnataka detail underneath it. Third, the provisional marker rides inside the period itself - (P) - so a revised figure never impersonates a final one downstream.

Every other record repeats this anatomy: geography key, mineral, period, quantity, value, and where relevant the count of mines or the cited price source.

Nine documented fields carry the analytical payload, definitions verified during research, grouped into four families: geography (State/District), extraction (ore produced in tonnes, average grade in grams per tonne), output and money (quantity in kilograms, value in thousands of rupees), and the inventory and price complex (UNFC reserves and remaining resources, reporting mine counts, Average Sale Price with its cited source).

That last family is the quiet differentiator. Reserve columns arrive pre-classified to the UNFC scheme with the inventory cut-off date attached, and every Average Sale Price row names the benchmark it was set against - so a royalty model inherits its provenance instead of reconstructing it.

Six groups sit beside the core dictionary and get mapped to your use case at sampling:

• District splits - the sub-state rows behind each state total, where district-level tables resolve further than the headline cut.
• World comparison tables - world reserves and mine production by country, carried inside each metal review for context.
• Trade legs - the import and export tables attached to individual metal reviews.
• Principal producers - named producer lists from the metals & alloys reviews.
• Sector splits - public versus private breakdowns behind production and mine-count cells.
• Corrigenda and prior-year comparatives - correction notices issued between editions, plus previous-period columns printed alongside current ones.

Name the ones you want when you request the sample; they arrive as ordinary columns in the same rows, not as a side file.

Geography - all of India, resolved three ways: national totals, state breakdowns and district detail, with public versus private sector splits alongside. World comparison tables by country ride inside each metal review, so Indian figures always have their global context within arm's reach.

Temporal - yearbook editions run 2015 through 2024, with data year 2023-24 the latest full annual picture. The monthly production layer reaches back to 2013 and runs forward through the most recent observed issue, May 2026; the average-sale-price tables continue through June 2026. Two cadences in one record, matched to the two jobs they serve: the annual volume for structure, the monthly issues for movement.

Granularity - national, state and district totals by mineral and by sector. Annual for the yearbook layer, monthly for the production-statistics and price layers. Units stay honest per mineral - kilograms of metal content for gold and silver, tonnes for ore - and travel with every figure.

API, files, or your warehouse. Daily, weekly, or hourly.

Name the metals, the geography level and the period window when you request the sample - the full three-series estate, a gold-and-silver-only cut, or the monthly price tables on their own. The sample ships first either way; the ongoing feed lands on whatever cadence your models need, shaped to the scope you named rather than as an undifferentiated dump.

A national statistical record earns its keep in five jobs:

• Royalty and pricing teams - the Average Sale Price tables exist precisely because Indian royalty computation needs a defensible benchmark, and every row cites its own.
• Investors and quant researchers - Indian gold and silver supply panels with by-product and bullion flows kept separate, enough history to backtest against.
• Market researchers and consultants - the base table for India-facing metals sizing, from one editorial hand rather than stitched aggregator estimates.
• Competitive intelligence teams - monthly production movement by state and mineral evidences demand and supply shifts in client briefs with numbers, not adjectives.
• Data scientists - typed numeric columns with provisional markers, so ingestion starts at configuration rather than reconstruction.

Deeper guidance sits on the market researchers, investors & quants and journalists & academics persona pages.

Market Researchers & Consultants get the qualifying questions answered from the coverage alone - scope, geography levels and years available in one place. Investors & Quant Researchers get a supply panel where primary output, bullion and by-product recovery never blur together, at monthly resolution where it matters. Data Scientists & ML Engineers get typed rows whose provisional markers declare themselves, so a revision never masquerades as a final figure mid-pipeline. Journalists, Academics & Students get the original statistical record with attribution to a Government of India agency. Competitive Intelligence & Product Teams get change detection across whole states and sectors rather than single companies. Start from the precious metals & minerals data hub, then read vs MetalpriceAPI for where official production depth beats spot-price breadth.

Provenance note - compiled by the Indian Bureau of Mines under the Ministry of Mines, the Government of India's official mineral statistics agency. One editorial hand across all three series is why the state-district-sector shape holds from edition to edition, and why the bilingual presentation around the tables never leaks into the figures themselves.

Methodology note - the compilers flag their own caveats and the fields preserve them: provisional markers on the period, cited sources on every benchmarked price, UNFC classification dates on inventory tables. Read quantity together with its period marker rather than alone, and treat the compilers' discretion note as part of the data, not fine print.

Completeness note - Datadory scores this record 8/10, and the nine-field dictionary above maps fully to verified definitions. District-level depth varies by mineral and review; availability of specific district splits is confirmed at sampling rather than asserted here.

Where to go next - pair the Indian national record with a century-scale global counterpart and the wider market lens: BGS MineralsUK for the long world series, the Silver Institute for silver market balances, USGS Mineral Commodity Summaries for the current-year global read. The glossary entries below define the vocabulary the tables use.