Data Dictionary

ID
id
Type
int4
Label
index

ID
year
Type
text
Label
Year

ID
state_name
Type
text
Label
State Name

ID
state_code
Type
text
Label
State Code

ID
district_name
Type
text
Label
District Name

ID
district_code
Type
text
Label
District Code

ID
registration_circles
Type
text
Label
Registration Circles

ID
male_below_12_years
Type
numeric
Label
Male Below 12 Years

ID
male_12_years_to_16_years
Type
numeric
Label
Male 12 Years To 16 Years

ID
male_16_years_to_18_years
Type
numeric
Label
Male 16 Years To 18 Years

ID
male_children
Type
numeric
Label
Male Children

ID
male_18_years_and_above
Type
numeric
Label
Male 18 Years And Above

ID
female_below_12_years
Type
numeric
Label
Female Below 12 Years

ID
female_12_years_to_16_years
Type
numeric
Label
Female 12 Years To 16 Years

ID
female_16_years_to_18_years
Type
numeric
Label
Female 16 Years To 18 Years

ID
female_children
Type
numeric
Label
Female Children

ID
female_18_years_and_above
Type
numeric
Label
Female 18 Years And Above

ID
transgender_below_12_years
Type
numeric
Label
Transgender Below 12 Years

ID
transgender_12_years_to_16_years
Type
numeric
Label
Transgender 12 Years To 16 Years

ID
transgender_16_years_to_18_years
Type
numeric
Label
Transgender 16 Years To 18 Years

ID
transgender_children
Type
numeric
Label
Transgender Children

ID
transgender_18_years_and_above
Type
numeric
Label
Transgender 18 Years And Above

Additional Information

Field Value
Data last updated September 5, 2024
Metadata last updated September 5, 2024
Created September 4, 2024
Format CSV
License No License Provided
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 updated2024-08-01 00:00:00
Data retreival date2024-07-01 00:00:00
Datastore activeTrue
District no753
FrequencyYearly
GranularityDistrict
Has viewsTrue
Id25119741-f6c4-4242-b238-bb195c4ae530
Idp readyFalse
Lgd mappingyes
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.
Mimetypetext/csv
No indicators15
Package ide311a510-ce48-4f4c-baf6-0ec5f9278285
Position10
Size225.7 KiB
Skuncrb-cii_missing_persons-dt-yr-rct
Stateactive
States uts no36
Tags['Missing Persons', 'NCRB', 'Gender Statistics', 'Age Group', 'Crime Analysis', 'Vulnerable Populations']
Url typeupload
Years covered2021-2022
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-rct
Dataset Frequency Yearly
Years Covered 2021-2022
No of States/UT(s) 36
No of Districts 753
No of Tehsils/blocks
No of Gram Panchayats
Additional Information nan
Number of Indicators 15
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 No
LGD Mapping Yes