Data Dictionary

Column Type Label Description
id int4 index
year date Year
state_name text State Name
state_code text State Code
district_name text District Name
district_code text District Code
registeration_circles text Case Registered in Circle
total_male numeric Total Male
male_below_12_years numeric Male_Below 12 years
male_12_years_and_above_below_16_years numeric Male_12 years & Above_Below 16 years
male_16_years_and_above_below_18_years numeric Male_16 years & Above_Below 18 years
male_children numeric Male_Children
male_18_years_and_above numeric Male_18 years & Above
total_female numeric Total Female
female_below_12_years numeric Female_Below 12 years
female_12_years_and_above_below_16_years numeric Female_12 years & Above_Below 16 years
female_16_years_and_above_below_18years numeric Female_16 years & Above_Below 18 years
female_children numeric Female_Children
female_18_years_and_above numeric Female_18 years & Above
total_transgender numeric Total Transgender
transgender_below_12_years numeric Transgender_Below 12 years
transgender_12_years_and_above_below_16_years numeric Transgender_12 years & Above_Below 16 years
transgender_16_years_and_above_below_18_years numeric Transgender_16 years & Above_Below 18 years
transgender_children numeric Transgender_Children
transgender_18_years_and_above numeric Transgender_18 years & Above
grand_total numeric Grand Total
total_below_12_years numeric Total_Below 12 years
total_12_years_and_above_below_14_years numeric Total_12 years & Above_Below 14 years
total_14_years_and_above_below_18_years numeric Total_14 years & Above_Below 18 years
total_children numeric Total_Children
total_18_years_and_above numeric Total_18 years & Above

Additional Information

Field Value
Data last updated June 24, 2024
Metadata last updated June 25, 2024
Created June 24, 2024
Format CSV
License Open Data Commons Attribution License
Additional infonan
Data extraction pagehttps://ncrb.gov.in/crime-in-india.html
Data insightsData 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 updated2,021
Data retreival date2023-10-01 00:00:00
Datastore activeTrue
District no12
FrequencyYearly
GranularityDistrict
Has viewsTrue
Idbb8f0846-002c-4156-ada1-65052e07048b
Idp readyTrue
MethodologyThe 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 indicators24
Package iddb72aca9-7907-456c-a7f5-407ecd3d0fc6
Position7
Size3.4 KiB
Skuncrb-cii_missing_persons-dt-yr-him
Stateactive
States uts no1
Url typeupload
Years covered2,021
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.
Similar Resources
Granularity Level District
Data Extraction Page https://ncrb.gov.in/crime-in-india.html
Data Retreival Date 2023-10-01 00:00:00
Data Last Updated 2021
Sku ncrb-cii_missing_persons-dt-yr-him
Dataset Frequency Yearly
Years Covered 2021.0
No of States/UT(s) 1
No of Districts 12
No of Tehsils/blocks
No of Gram Panchayats
Additional Information nan
Number of Indicators 24
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