SHG Financial and Member Profile Details
This dataset provides an extensive and nuanced profile of Self-Help Groups (SHGs) across diverse geographic and socio-economic contexts. It includes detailed information on the SHG's location, specifying the state, district, block, Gram Panchayat, and village, alongside a unique SHG identifier and its name. Key administrative details such as the date of formation, type of SHG, promoting entity, and banking information—including the bank name, branch, and account opening date—are also recorded. The dataset meticulously documents membership demographics, including total membership counts, gender distribution, and classifications by social categories such as Scheduled Caste, Scheduled Tribe, Other Backward Classes, and Other Social Categories. Additionally, it captures data on members with disabilities, both self-disabled and those with disabled family members, and provides insights into religious affiliations (Hindu, Christian, Muslim, Sikh, Buddhist, Jain, Parsi) and economic status, distinguishing between Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor under the PIP category.
Metadata - | Variable Name | Variable Description | Variable Type | Unit Of Measurement | |-----------------------------------|---------------------------------------------------------------|---------------|---------------------| | state_name | State Name | TEXT | | | district_name | District Name | TEXT | | | block_name | Block Name | TEXT | | | gp_name | Gram Panchayat Name | TEXT | | | village_name | Village Name | TEXT | | | shg_name | Self Help Group Name | TEXT | | | shg_id | Self Help Group ID | TEXT | | | formation_date | Date of Formation of SHG | DATE | | | shg_type | Type of SHG | TEXT | | | promoted_by | SHG Promoted By | TEXT | | | bank_name | Name of the bank where SHG is registered | TEXT | | | bank_branch | Name of the bank branch where SHG is registered | TEXT | | | acc_opening_date | Date of opening of Bank Account | TEXT | | | total_members | Number of members in SHG | NUMERIC | Numerical | | female | Number of female members in SHG | NUMERIC | Numerical | | male | Number of male members in SHG | NUMERIC | Numerical | | sc | Number of Scheduled Caste members in SHG | NUMERIC | Numerical | | st | Number of Scheduled Tribe members in SHG | NUMERIC | Numerical | | obc | Number of members belonging to Other Backward Classes | NUMERIC | Numerical | | other_category | Number of members belonging to Other Social Categories | NUMERIC | Numerical | | disabled | Number of members with disabilities | NUMERIC | Numerical | | family_mem_disabled | Number of members with a disabled family member | NUMERIC | Numerical | | hindu | Number of Hindu members | NUMERIC | Numerical | | christian | Number of Christian members | NUMERIC | Numerical | | muslim | Number of Muslim members | NUMERIC | Numerical | | sikh | Number of Sikh members | NUMERIC | Numerical | | buddhist | Number of Buddhist members | NUMERIC | Numerical | | jain | Number of Jain members | NUMERIC | Numerical | | parsi | Number of Parsi members | NUMERIC | Numerical | | apl | Number of members categorized as Above Poverty Line (APL) | NUMERIC | Numerical | | bpl | Number of members categorized as Below Poverty Line (BPL) | NUMERIC | Numerical | | pop | Number of members categorized as Poorest of the Poor under PIP category | NUMERIC | Numerical | | poor | Number of members categorized as Poor under PIP category | NUMERIC | Numerical |
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Additional Information
| Field | Value |
|---|---|
| Data last updated | December 31, 2024 |
| Metadata last updated | February 5, 2025 |
| Created | December 31, 2024 |
| Format | unknown |
| License | License not specified |
| Additional info | Data for Ladakh not available on source |
| Data extraction page | https://nrlm.gov.in/shgReport.do?methodName=showMojorityStateWise |
| Data insights | The dataset offers a wealth of insights into the operational and demographic characteristics of Self-Help Groups (SHGs). Analyzing the geographic distribution, including state, district, block, Gram Panchayat, and village information, reveals the spatial spread and concentration of SHGs, highlighting regions with varying levels of SHG activity. This can inform targeted support and resource allocation. The formation dates and SHG types enable the tracking of trends over time, shedding light on the growth patterns and focus areas of SHG initiatives. Membership data, including total numbers, gender distribution, and socio-economic classifications such as Scheduled Caste, Scheduled Tribe, and Other Backward Classes, provides a nuanced understanding of the demographic composition and inclusivity of SHGs. Insights into disability status and economic classifications, such as Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor, further reveal the socio-economic challenges faced by SHG members. Overall, this dataset facilitates a comprehensive analysis of SHG dynamics, supporting evidence-based policy-making and strategic planning aimed at enhancing the effectiveness and reach of SHG programs. |
| Data last updated | 18-08-2024 |
| Data retreival date | 18-08-2024 |
| Datastore active | False |
| District no | 740 |
| Frequency | Other |
| Gp no | 242,220 |
| Granularity | SHG |
| Has views | False |
| Id | 796bbee7-9743-49c6-bb1d-d460c475786d |
| Idp ready | False |
| Lgd mapping | no |
| Methodology | Data collection for Self-Help Groups (SHGs) under the National Rural Employment Guarantee Scheme (NRLM) follows a structured methodology to ensure comprehensive and accurate information. The process begins with collecting basic SHG details, including state, district, block, Gram Panchayat, village, SHG name, formation date, type, promotion entity, and bank account information. Essential data points such as meeting frequency, bank linkage, savings per member, and loan account details are recorded. The methodology also involves assessing the preparedness of SHGs through questions about micro planning, basic training, bookkeeping practices, and the identification of a bookkeeper.To support financial inclusion, the data collection framework includes guidelines and multiple handbooks outlining the roles and responsibilities of mission units at various levels. These handbooks provide standardized procedures and best practices for ensuring effective SHG bank linkages and financial management. The collected data is then used to analyze SHG performance and impact, informing strategic decisions and program enhancements. |
| No indicators | 20 |
| Package id | 4241bc8e-171e-4406-9d5a-fd2b950ff0db |
| Position | 0 |
| Sku | mord-nrlm_social_category_wise-shg-ot-abc |
| State | active |
| States uts no | 33 |
| Methodology | Data collection for Self-Help Groups (SHGs) under the National Rural Employment Guarantee Scheme (NRLM) follows a structured methodology to ensure comprehensive and accurate information. The process begins with collecting basic SHG details, including state, district, block, Gram Panchayat, village, SHG name, formation date, type, promotion entity, and bank account information. Essential data points such as meeting frequency, bank linkage, savings per member, and loan account details are recorded. The methodology also involves assessing the preparedness of SHGs through questions about micro planning, basic training, bookkeeping practices, and the identification of a bookkeeper.To support financial inclusion, the data collection framework includes guidelines and multiple handbooks outlining the roles and responsibilities of mission units at various levels. These handbooks provide standardized procedures and best practices for ensuring effective SHG bank linkages and financial management. The collected data is then used to analyze SHG performance and impact, informing strategic decisions and program enhancements. |
| Indicators | [] |
| Similar Resources | |
| Granularity Level | SHG |
| Data Extraction Page | https://nrlm.gov.in/shgReport.do?methodName=showMojorityStateWise |
| Data Retreival Date | 18-08-2024 |
| Data Last Updated | 18-08-2024 |
| Sku | mord-nrlm_social_category_wise-shg-ot-abc |
| Dataset Frequency | Other |
| Years Covered | |
| No of States/UT(s) | 33 |
| No of Districts | 740 |
| No of Tehsils/blocks | |
| No of Gram Panchayats | 242220 |
| Additional Information | Data for Ladakh not available on source |
| Number of Indicators | 20 |
| Insights from the dataset | The dataset offers a wealth of insights into the operational and demographic characteristics of Self-Help Groups (SHGs). Analyzing the geographic distribution, including state, district, block, Gram Panchayat, and village information, reveals the spatial spread and concentration of SHGs, highlighting regions with varying levels of SHG activity. This can inform targeted support and resource allocation. The formation dates and SHG types enable the tracking of trends over time, shedding light on the growth patterns and focus areas of SHG initiatives. Membership data, including total numbers, gender distribution, and socio-economic classifications such as Scheduled Caste, Scheduled Tribe, and Other Backward Classes, provides a nuanced understanding of the demographic composition and inclusivity of SHGs. Insights into disability status and economic classifications, such as Above Poverty Line (APL), Below Poverty Line (BPL), and Poorest of the Poor, further reveal the socio-economic challenges faced by SHG members. Overall, this dataset facilitates a comprehensive analysis of SHG dynamics, supporting evidence-based policy-making and strategic planning aimed at enhancing the effectiveness and reach of SHG programs. |
| IDP Ready | No |
| LGD Mapping | No |