Districtwise Missing Persons 2017-2020
The "Districtwise Missing Persons 2021" dataset provides comprehensive data regarding individuals who went missing in different states and districts of India during the year 2021. The dataset segregates the missing persons based on gender (Male, Female, Transgender) and further categorizes them based on age groups. This helps in understanding the demographics of missing persons on a district and state level for the mentioned year.
Dicionario de datos
- ID
- id
- Tipo
- int4
- Etiqueta
- index
- ID
- year
- Tipo
- text
- Etiqueta
- year
- ID
- state_name
- Tipo
- text
- Etiqueta
- state_name
- ID
- state_code
- Tipo
- text
- Etiqueta
- state_code
- ID
- district_name
- Tipo
- text
- Etiqueta
- district_name
- ID
- district_code
- Tipo
- text
- Etiqueta
- district_code
- ID
- registration_circles
- Tipo
- text
- Etiqueta
- registration_circles
- ID
- male_below_5_years
- Tipo
- text
- Etiqueta
- male_below_5_years
- ID
- male_5_to_14_years
- Tipo
- numeric
- Etiqueta
- male_5_to_14_years
- ID
- male_14_to_18_years
- Tipo
- numeric
- Etiqueta
- male_14_to_18_years
- ID
- male_18_to_30_years
- Tipo
- numeric
- Etiqueta
- male_18_to_30_years
- ID
- male_30_to_45_years
- Tipo
- numeric
- Etiqueta
- male_30_to_45_years
- ID
- male_45_to_60_years
- Tipo
- numeric
- Etiqueta
- male_45_to_60_years
- ID
- male_60_years_and_above
- Tipo
- numeric
- Etiqueta
- male_60_years_and_above
- ID
- female_below_5_years
- Tipo
- numeric
- Etiqueta
- female_below_5_years
- ID
- female_5_to_14_years
- Tipo
- numeric
- Etiqueta
- female_5_to_14_years
- ID
- female_14_to_18_years
- Tipo
- numeric
- Etiqueta
- female_14_to_18_years
- ID
- female_18_to_30_years
- Tipo
- numeric
- Etiqueta
- female_18_to_30_years
- ID
- female_30_to_45_years
- Tipo
- numeric
- Etiqueta
- female_30_to_45_years
- ID
- female_45_to_60_years
- Tipo
- numeric
- Etiqueta
- female_45_to_60_years
- ID
- female_60_years_and_above
- Tipo
- numeric
- Etiqueta
- female_60_years_and_above
- ID
- trangender_below_5_years
- Tipo
- numeric
- Etiqueta
- trangender_below_5_years
- ID
- trangender_5_to_14_years
- Tipo
- numeric
- Etiqueta
- trangender_5_to_14_years
- ID
- trangender_14_to_18_years
- Tipo
- numeric
- Etiqueta
- trangender_14_to_18_years
- ID
- trangender_18_to_30_years
- Tipo
- numeric
- Etiqueta
- trangender_18_to_30_years
- ID
- trangender_30_to_45_years
- Tipo
- numeric
- Etiqueta
- trangender_30_to_45_years
- ID
- trangender_45_to_60_years
- Tipo
- numeric
- Etiqueta
- trangender_45_to_60_years
- ID
- transgender_60_years_and_above
- Tipo
- numeric
- Etiqueta
- transgender_60_years_and_above
Información adicional
| Campo | Valor |
|---|---|
| Última actualización de datos | 4 de setembro de 2024 |
| Última actualización de metadatos | 5 de setembro de 2024 |
| Creado | 4 de setembro de 2024 |
| Formato | CSV |
| Licenza | Non se fornece ningunha licenza |
| Additional info | nan |
| Data extraction page | https://ncrb.gov.in/crime-in-india.html |
| Data insights | Data Insights that can be drawn:Distribution of missing persons based on gender across different states and districts.Age-wise breakdown of missing persons which can shed light on the age groups that are most vulnerable.Comparative analysis between states and districts to identify regions with high numbers of missing persons.Gender-wise distribution in specific age groups to understand if there's a significant disparity.Analysis of total missing children vs. adults can help in strategizing preventive measures for the vulnerable age groups. |
| Data last updated | 2024-08-01 00:00:00 |
| Data retreival date | 2024-07-01 00:00:00 |
| Datastore active | True |
| District no | 731 |
| Frequency | Yearly |
| Granularity | District |
| Has views | True |
| Id | 90b83f06-7f08-4bc2-8ffb-4859129476bb |
| Idp ready | True |
| Lgd mapping | yes |
| Methodology | The dataset is sourced from the official website of the National Crime Records Bureau (NCRB) of India. NCRB collates this data from various state and district police records. It is important to note that the data might be subject to changes based on further verifications and updates from respective state and district authorities. |
| No indicators | 32 |
| Package id | e311a510-ce48-4f4c-baf6-0ec5f9278285 |
| Position | 9 |
| Size | 508,5 KiB |
| Sku | ncrb-cii_missing_persons-dt-yr-prv |
| State | active |
| States uts no | 36 |
| Url type | upload |
| Years covered | 2017-2020 |
| Methodology | The dataset is sourced from the official website of the National Crime Records Bureau (NCRB) of India. NCRB collates this data from various state and district police records. It is important to note that the data might be subject to changes based on further verifications and updates from respective state and district authorities. |
| Indicators | |
| Similar Resources | |
| Granularity Level | District |
| Data Extraction Page | https://ncrb.gov.in/crime-in-india.html |
| Data Retreival Date | 2024-07-01 00:00:00 |
| Data Last Updated | 2024-08-01 00:00:00 |
| Sku | ncrb-cii_missing_persons-dt-yr-prv |
| Dataset Frequency | Yearly |
| Years Covered | 2017-2020 |
| No of States/UT(s) | 36 |
| No of Districts | 731 |
| No of Tehsils/blocks | |
| No of Gram Panchayats | |
| Información adicional | nan |
| Number of Indicators | 32 |
| Insights from the dataset | Data Insights that can be drawn:Distribution of missing persons based on gender across different states and districts.Age-wise breakdown of missing persons which can shed light on the age groups that are most vulnerable.Comparative analysis between states and districts to identify regions with high numbers of missing persons.Gender-wise distribution in specific age groups to understand if there's a significant disparity.Analysis of total missing children vs. adults can help in strategizing preventive measures for the vulnerable age groups. |
| IDP Ready | Yes |
| LGD Mapping | Yes |
| Mapping Status % |