Data Dictionary

Mer information

Fält	Värde
Data senast uppdaterad	2 januari 2024
Metadata senast uppdaterad	19 december 2025
Skapad	8 oktober 2023
Format	CSV
Licens	Open Data Commons Attribution License
Additional info	nan
Data extraction page	https://missionantyodaya.nic.in/ma2019/preloginStateInfrastructureReports2019.html
Data insights	Data insights that can be drawn: Demographic Analysis: Understand population distribution across different states, districts, and blocks, and identify gender ratios at these levels. Infrastructure Insights: Gauge the availability and distribution of essential amenities such as banks, ATMs, internet connectivity, and road infrastructure. Utility Services: Analyze the availability and frequency of electricity for domestic and MSME units, water supply infrastructure, and the use of clean energy sources. Public Amenities: Determine the availability of public transportation, markets, post offices, and public information boards. Educational & Recreational Facilities: Understand the accessibility to various educational institutions, libraries, sports, and recreational facilities at the village level. Healthcare Facilities: Examine the healthcare infrastructure, including the availability of CHCs, PHCs, sub-centres, and the proximity to these facilities. Drainage System Analysis: Gauge the type and quality of drainage facilities available.
Data last updated	2019-2020
Data retreival date	2019-2020
Datastore active	True
District no	711
Frequency	Yearly
Geo columns	['state_code', 'district_code', 'block_code', 'gp_code']
Gp no	267 126
Granularity	Panchayat
Has views	True
Id	382942ce-d369-48b4-925b-476d0483f65f
Idp ready	True
Lgd mapping	yes
Methodology	Data for this dataset appears to be gathered through direct surveys conducted at the Gram Panchayat level across different states in India. The data points seem to be primarily quantitative in nature, possibly derived from village council reports or direct survey metrics.
Mimetype	text/csv
No indicators	87
Package id	827d5a47-647f-4c00-8b21-a17ea43ce450
Position	2
Size	114,9 MiB
Sku	mord-mission_antyodaya-gp-ot-bmd
State	active
States uts no	32
Tehsil no	7 104
Url type	upload
Village no	648 245
Years covered	2 020
Methodology	Data for this dataset appears to be gathered through direct surveys conducted at the Gram Panchayat level across different states in India. The data points seem to be primarily quantitative in nature, possibly derived from village council reports or direct survey metrics.
Indicators
Similar Resources
Granularity Level	Panchayat
Data Extraction Page	https://missionantyodaya.nic.in/ma2019/preloginStateInfrastructureReports2019.html
Data Retreival Date	2019-2020
Data Last Updated	2019-2020
Sku	mord-mission_antyodaya-gp-ot-bmd
Dataset Frequency	Yearly
Years Covered	2020.0
No of States/UT(s)	32
No of Districts	711
No of Tehsils/blocks	7104
No of Gram Panchayats	267126
Mer information	nan
Number of Indicators	87
Insights from the dataset	Data insights that can be drawn: Demographic Analysis: Understand population distribution across different states, districts, and blocks, and identify gender ratios at these levels. Infrastructure Insights: Gauge the availability and distribution of essential amenities such as banks, ATMs, internet connectivity, and road infrastructure. Utility Services: Analyze the availability and frequency of electricity for domestic and MSME units, water supply infrastructure, and the use of clean energy sources. Public Amenities: Determine the availability of public transportation, markets, post offices, and public information boards. Educational & Recreational Facilities: Understand the accessibility to various educational institutions, libraries, sports, and recreational facilities at the village level. Healthcare Facilities: Examine the healthcare infrastructure, including the availability of CHCs, PHCs, sub-centres, and the proximity to these facilities. Drainage System Analysis: Gauge the type and quality of drainage facilities available.
IDP Ready	Yes
LGD Mapping	Yes
Mapping Status %
Geo Columns	['state_code', 'district_code', 'block_code', 'gp_code']