Data
Economic_Census_Delhi

Economic_Census_Delhi

active ARFF Public Domain (CC0) Visibility: public Uploaded 31-05-2024 by Iwo Godzwon
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Description: The delhi_state.csv dataset is a structured collection of data associated with various economic, demographic, and social attributes of areas within Delhi state, India. This extensive dataset provides insight into different dimensions including but not limited to the administration (State, District, Tehsil), workforce composition (WC, EB, EBX, BACT, NIC3, TOTAL_WORKER), household characteristics (C_HOUSE, IN_HH, OWN_SHIP_C), personal demographics (SEX, SG, RELIGION), and other assorted metrics like T_V (Total Value), HLOOM_ACT (Handloom Activity), NOP (Number of Persons), SOF (Source of Finance), M_H (Male Headed Households), F_H (Female Headed Households), M_NH (Male Non-headed Households), F_NH (Female Non-headed Households), and the operational SECTOR of the workforce. Key identifiers like the DISTRICT code provide locational specificity enhancing the dataset's utility for regional analysis. Attribute Description: - State, District, Tehsil: Administrative identifiers. - T_V: Numeric, represents a Total Value (could be economic or demographic in nature). - WC, EB, BACT, NIC3, TOTAL_WORKER: Workforce composition metrics, numeric. - EBX, HLOOM_ACT, IN_HH, C_HOUSE, OWN_SHIP_C: Economic and household characteristic indicators, binary or numeric. - SEX, SG, RELIGION: Demographic attributes, coded numerically. - NOP, SOF: Numeric, detailing household composition and financial sources. - M_H, F_H, M_NH, F_NH: Household headship indicators, numeric. - SECTOR, DISTRICT: Numeric codes reflecting the area of employment and locational identification. Use Case: This dataset is invaluable for policymakers, researchers, and NGOs focusing on urban planning, socioeconomic development, and demographic studies within Delhi. It can facilitate targeted interventions, policy formulation, and understand community-specific needs. Additionally, socio-economic researchers can analyze workforce dynamics, household structures, and demographic trends to derive meaningful insights into the social fabric of Delhi.

25 features

Statestring1 unique values
0 missing
Districtnominal11 unique values
0 missing
Tehsilnominal7 unique values
0 missing
T_Vnumeric227 unique values
0 missing
WCnumeric272 unique values
0 missing
EBnumeric416 unique values
0 missing
EBXnominal5 unique values
0 missing
C_HOUSEnominal2 unique values
0 missing
IN_HHstring12 unique values
0 missing
BACTstring22 unique values
0 missing
NIC3nominal219 unique values
0 missing
HLOOM_ACTnominal2 unique values
0 missing
OWN_SHIP_Cnominal8 unique values
0 missing
SEXnominal4 unique values
0 missing
SGnominal5 unique values
0 missing
RELIGIONnominal9 unique values
0 missing
NOPnominal3 unique values
0 missing
SOFnumeric6 unique values
0 missing
M_Hnumeric342 unique values
0 missing
F_Hnumeric180 unique values
0 missing
M_NHnumeric41 unique values
0 missing
F_NHnumeric26 unique values
0 missing
TOTAL_WORKERnumeric390 unique values
0 missing
SECTORnominal2 unique values
0 missing
DISTRICTnominal11 unique values
0 missing

19 properties

875308
Number of instances (rows) of the dataset.
25
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
9
Number of numeric attributes.
13
Number of nominal attributes.
12
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
36
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
52
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
3
Number of binary attributes.

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