National averages hide state gaps. State averages hide something larger.
Data year: Derived — inherits the vintage of its inputs · Source: Computed from source indicators · Updated: Rebuilt when an input changesIn preparation
National averages hide state gaps. State averages hide something larger.
On most development indicators, the spread between the best and worst district inside a single large Indian state is wider than the spread between countries at different income levels. A state-level number is an average of that spread, and planning is done at district level.
Publishing the within-state distribution rather than the state mean changes which places look like they need attention. That is uncomfortable, and it is the point.
These are the indicators this topic is built from. Each names its source and the year that source refers to, because an official figure is not the same thing as a current one.
| Indicator | Unit | Source and year |
|---|---|---|
| Within-state district spread | coefficient of variation | Computed from source indicatorsData year: Derived — inherits the vintage of its inputs |
| Income share of the bottom 40% | % | Household consumption surveyData year: 2023-24 |
| Best and worst district gap | index points | Computed from source indicatorsData year: Derived — inherits the vintage of its inputs |
| Aspirational districts progress | score | NITI Aayog Champions of ChangeData year: 2026 (monthly ranking) |
A distribution view for any indicator on the platform: not one number per state, but the range inside it.
The brief above is written and the sources are identified. What remains is the data build. Until it publishes, no figure for this topic appears anywhere on DataSpeaks — we would rather show nothing than show a placeholder.
Where a source has not reported for a recent year, the gap is shown as a gap. We do not interpolate to make a series look continuous or a map look complete. Where two agencies publish different figures for the same thing, both appear and we say which is which.
Charts from this topic may be reused with credit to DataSpeaks and to the original source named above. The underlying data remains under its own licence — most Government of India datasets permit reuse with attribution, some survey microdata does not.
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