NetaRecord
Every sitting member

All members

Affidavits, declared assets, criminal cases and attendance, filed against the person who filed them.

Area data

All indicators

Crime, population and spending figures for the state and district a seat sits in, from the agency that published them.

How this is built

API reference

What each figure comes from, what it cannot tell you, and what is still missing from the record.

Area indicators

Figures about places, not people.

Crime, safety, education and population data for states and districts, pulled from the Open Government Data platform. These describe a geography, never a legislator. There is no join in this database from a crime figure to a member, and the API refuses to return one.

Why that matters. A constituency with a high reported crime figure is not evidence about the person who represents it. Reported crime measures reporting as much as incidence: a state with better policing and more willing complainants can look worse than one where offences go unrecorded.
Population

Projected mid-year population

Mid-year population in lakhs, as projected by the publisher for the year the rate beside it describes. Published by National Crime Records Bureau, 2022 to 2023.

382383384386387 20222023 2022: 383 2023: 387

2022: 383 to 2023: 387

Average across all reporting states. Up 1% between the first and last year on record, which is arithmetic on two figures rather than a trend. The vertical axis does not start at zero, because every value sits well above it. Hover or tab through the points to read each year.

How to read this

The average across reporting states

What it measures
Mid-year population in lakhs, as projected by the publisher for the year the rate beside it describes.
What moves it
Whatever the publisher measures changing, and any change to how they measure it.
What it cannot show
Anything about a single place. A national figure hides states moving in opposite directions.

Years with fewer than twenty reporting states are left out, so a partial year cannot look like a collapse.

Rank State or union territory 2023 Relative Change since 2022
1 Uttar Pradesh 2,365
+1%
2 Bihar 1,274
+1%
3 Maharashtra 1,267
+1%
4 West Bengal 992
+0%
5 Madhya Pradesh 869
+1%
6 Rajasthan 813
+1%
7 Tamil Nadu 769
+0%
8 Gujarat 718
+1%
9 Karnataka 678
+1%
10 Andhra Pradesh 532
+0%
11 Odisha 464
+1%
12 Jharkhand 396
+1%
13 Telangana 381
+1%
14 Assam 358
+1%
15 Kerala 358
+0%
16 Punjab 308
+1%
17 Haryana 303
+1%
18 Chhattisgarh 303
+1%
19 Delhi 215
+2%
20 Jammu and Kashmir 136
+1%
21 Uttarakhand 117
+1%
22 Himachal Pradesh 75
+1%
23 Tripura 42
+1%
24 Meghalaya 34
+1%
25 Manipur 32
+1%
26 Nagaland 22
+1%
27 Puducherry 17
+2%
28 Goa 16
+1%
29 Arunachal Pradesh 16
+1%
30 Dadra and Nagar Haveli and Daman and Diu 13
+8%
31 Mizoram 12
+1%
32 Chandigarh 12
+2%
33 Sikkim 7
+1%
34 Andaman and Nicobar Islands 4
0%
35 Ladakh 3
0%
36 Lakshadweep 1
0%
Figures describe the state, not any legislator of it. Ranked by the most recent year on record. The change column is arithmetic on the first and last published figures, not a trend estimate.

Every row in this table comes from one place: api.data.gov.in Published by National Crime Records Bureau.

Loaded series

11 of 39 with data

Crime

Population

Policing and justice

Defined but not yet loaded

28 series

These series are defined with their unit, direction and caveat, so the interface is ready for them. They are empty because the source resource has not been imported yet, not because the figure is zero. District and city figures in particular are published unevenly by year, and where only a state figure exists this database stores only a state figure.

Crimes against womenRate per lakh womenRapeDomestic crueltyDowry deathsCrimes against childrenPOCSO casesBoys missingGirls missingVictimsFemale victimsMale victimsRescuedIPC casesMurderCyber crimeCommunal riotingPopulationSex ratioChild sex ratioLiteracyFemale literacyMale literacyLiteracy gapMPI povertyMPI intensityConviction rateChargesheet rate
Method

How these figures reach a seat page.

A constituency is not a district, so the overlap has to be stated rather than assumed.

Most parliamentary seats span several districts and most districts contain several assembly seats. Where a district figure is shown on a seat page, the districts it covers are named and the overlap is stated. Where only a state figure exists, the page says state rather than dividing a state number across districts.

Every rate here uses a 2011 Census denominator, because the 2021 Census has not been conducted. Rates for fast-growing districts are therefore overstated, and that is a limit of the source rather than a choice made here. Where a publisher gives both a count and a rate, both are stored so the rate can be recomputed and checked.

Full methodology and every source with its licence.

Sources and licences What is missing