One figure at a time.
There is no NetaRecord score. Ranking a legislator overall would mean deciding what a question is worth against a day of attendance, and that decision would be ours rather than the record's. Every table below answers one narrow question and names its document.
Who turned up to the most sittings?
Share of sittings the member was present for. A low figure can mean absence, illness or a ministerial post, and this page does not guess which. The average is 79% across the house.
Reporting window: Data corresponds to the period from 01-06-2019 to 10-02-2024.
| Rank | Member | Party | Seat | present | Source |
|---|---|---|---|---|---|
| 1 | Bhagirath Chaudhary | BJP | Ajmer | 100% | document |
| 2 | Mohan Mandavi | BJP | Kanker | 100% | document |
| 3 | Sunita Duggal | BJP | Sirsa | 100% | document |
| 4 | Ramesh Chander Kaushik | BJP | Sonipat | 100% | document |
| 5 | Dhal Singh Bisen | BJP | Balaghat | 99% | document |
| 6 | Jagdambika Pal | BJP | Domariyaganj | 99% | document |
| 7 | Brijendra Singh | BJP | Hisar | 99% | document |
| 8 | Chandra Sen Jadon | BJP | Firozabad | 99% | document |
| 9 | DNV Senthilkumar S. | DMK | Dharmapuri | 99% | document |
| 10 | Dhanush M Kumar | DMK | Tenkasi | 99% | document |
| 11 | Rama Devi | BJP | Sheohar | 99% | document |
| 12 | Manoj Kotak Kishorbhai | BJP | Mumbai North-East | 98% | document |
| 13 | Rajiv Pratap Rudy | BJP | Saran | 98% | document |
| 14 | Ram Swaroop Sharma | BJP | Mandi | 98% | document |
| 15 | Gopal Jee Thakur | BJP | Darbhanga | 98% | document |
| 16 | Kanumuru Raghu Rama Krishna Raju | YSRCP | Narsapuram | 98% | document |
| 17 | Rajendra Agrawal | BJP | Meerut | 98% | document |
| 18 | Sanghamitra Maurya | BJP | Badaun | 98% | document |
| 19 | Ram Shiromani | BSP | Shrawasti | 98% | document |
| 20 | Bholanath (B.P. Saroj) | BJP | Machhlishahr | 98% | document |
Both ends of every published series.
A state is not better or worse overall either. Each row is one indicator on its most recent published year, with the lowest and highest state on that figure. Which end is the good end depends on the indicator, so the column says so.
| Indicator | Year | Lowest | Highest | Better when |
|---|---|---|---|---|
| Total crimes | 2020 | Lakshadweep 147 | Tamil Nadu 13,77,681 | lower |
| Crime rate | 2020 | Dadra and Nagar Haveli and Daman and Diu 51 | Tamil Nadu 1,809 | lower |
| Violent crimes | 2023 | Lakshadweep 5 | Bihar 52,165 | lower |
| Violent crime rate | 2023 | Ladakh 5 | Manipur 447 | lower |
| Child drug offences | 2021 | Lakshadweep 0 | Madhya Pradesh 59 | lower |
| Trafficking cases | 2022 | Lakshadweep 0 | Telangana 391 | lower |
| Child victims | 2021 | Puducherry 0 | Odisha 497 | lower |
| SC and ST atrocities | 2022 | Puducherry 0 | Madhya Pradesh 2,979 | lower |
| UAPA cases | 2022 | Puducherry 0 | Jammu and Kashmir 371 | neither |
| Projected population | 2023 | Lakshadweep 1 | Uttar Pradesh 2,365 | neither |
| Chargesheet rate, violent | 2023 | Lakshadweep 33 | Kerala 94 | higher |