Aadhaar Saturation Report
The dataset, titled "Aadhaar Saturation Report," provides a detailed insight into the dissemination and reach of Aadhaar cards across different states in India. The Aadhaar card, an initiative by the Unique Identification Authority of India (UIDAI), serves as a unique identifier for residents of India. This report aids in understanding the reach and effectiveness of the Aadhaar program by tracking its progress across various states and age groups.
Data Dictionary
- ID
- id
- Type
- int4
- Label
- index
- ID
- date
- Type
- date
- Label
- Date
- ID
- state_name
- Type
- text
- Label
- State(s)
- ID
- state_code
- Type
- text
- Label
- State Code
- ID
- age_bucket
- Type
- text
- Label
- Age Group
- ID
- population
- Type
- numeric
- Label
- Projected Population
- ID
- num_of_aadhar_assigned
- Type
- numeric
- Label
- Aadhar cards issued
Additional Information
| Field | Value |
|---|---|
| Data last updated | September 23, 2024 |
| Metadata last updated | September 23, 2024 |
| Created | October 7, 2023 |
| Format | CSV |
| License | Open Data Commons Attribution License |
| Additional info | Annexure - Aadhaar Saturation report, Annual Reports - Unique Identification Authority of India |
| Data extraction page | https://uidai.gov.in/en/media-resources/uidai-documents/annual-reports.html |
| Data insights | Data Insights That Can Be Drawn: Trends Over Time: By studying the 'date' column, one can understand the rate at which Aadhaar cards are being distributed over time. Regional Analysis: Using the 'state_name' and 'state_code' columns, one can deduce which states have higher saturation of Aadhaar cards and which ones are lagging. Age Group Analysis: The 'age_bucket' column can be used to analyze the distribution and reach of Aadhaar cards amongst different age groups. Saturation Rate: By comparing 'population' against 'num_of_aadhar_assigned', one can calculate the percentage saturation of Aadhaar cards for the specified region and date. Identify Gaps: Any state or age group showing a significant gap between the 'population' and 'num_of_aadhar_assigned' might be areas that need more attention in terms of Aadhaar card distribution. |
| Data last updated | 2022-05-31 00:00:00 |
| Data retreival date | 2023-06-10 00:00:00 |
| Datastore active | True |
| Frequency | One Time |
| Granularity | State |
| Has views | True |
| Id | a6469771-2e77-4489-a749-01edd2e4027e |
| Idp ready | True |
| Lgd mapping | yes |
| Methodology | The dataset is sourced from the "Annexure - Aadhaar Saturation report" in the annual reports published by the Unique Identification Authority of India (UIDAI). UIDAI, under the Government of India, collates this data based on the Aadhaar card enrollments and their internal projected population figures. These figures help in assessing the percentage saturation of Aadhaar cards in the specified region for the given date. |
| Mimetype | text/csv |
| No indicators | 2 |
| Package id | 0f332a3f-d829-43cd-98d7-549c325e4192 |
| Position | 0 |
| Size | 7.5 KiB |
| Sku | meity-uidai_aadhaar_saturation-st-ot-aaa |
| State | active |
| States uts no | 36 |
| Tags | ['UIDAI', 'Aadhaar', 'Regional Analysis', 'Demographics', 'Saturation Report', 'Age Group Analysis'] |
| Url type | upload |
| Years covered | 2,022 |
| Methodology | The dataset is sourced from the "Annexure - Aadhaar Saturation report" in the annual reports published by the Unique Identification Authority of India (UIDAI). UIDAI, under the Government of India, collates this data based on the Aadhaar card enrollments and their internal projected population figures. These figures help in assessing the percentage saturation of Aadhaar cards in the specified region for the given date. |
| Indicators | |
| Similar Resources | |
| Granularity Level | State |
| Data Extraction Page | https://uidai.gov.in/en/media-resources/uidai-documents/annual-reports.html |
| Data Retreival Date | 2023-06-10 00:00:00 |
| Data Last Updated | 2022-05-31 00:00:00 |
| Sku | meity-uidai_aadhaar_saturation-st-ot-aaa |
| Dataset Frequency | One Time |
| Years Covered | 2022 |
| No of States/UT(s) | 36 |
| No of Districts | |
| No of Tehsils/blocks | |
| No of Gram Panchayats | |
| Additional Information | Annexure - Aadhaar Saturation report, Annual Reports - Unique Identification Authority of India |
| Number of Indicators | 2 |
| Insights from the dataset | Data Insights That Can Be Drawn: Trends Over Time: By studying the 'date' column, one can understand the rate at which Aadhaar cards are being distributed over time. Regional Analysis: Using the 'state_name' and 'state_code' columns, one can deduce which states have higher saturation of Aadhaar cards and which ones are lagging. Age Group Analysis: The 'age_bucket' column can be used to analyze the distribution and reach of Aadhaar cards amongst different age groups. Saturation Rate: By comparing 'population' against 'num_of_aadhar_assigned', one can calculate the percentage saturation of Aadhaar cards for the specified region and date. Identify Gaps: Any state or age group showing a significant gap between the 'population' and 'num_of_aadhar_assigned' might be areas that need more attention in terms of Aadhaar card distribution. |
| IDP Ready | Yes |
| LGD Mapping | Yes |