Mothers Deliveries
The "Meghalaya Deliveries" dataset is sourced from the Health and Family Welfare Department of Meghalaya. It provides information on deliveries in various regions of Meghalaya, including details such as the year of delivery, state name, district name, block name, and relevant codes. The dataset encompasses key metrics like the percentage of institutional deliveries in a block, the total number of deliveries, and the expected number of deliveries.
Data Dictionary
| Column | Type | Label | Description |
|---|---|---|---|
| id | int4 | index | |
| year | text | Year | |
| state_name | text | State Name | |
| state_code | text | State Code | |
| district_name | text | District Name | |
| district_code | text | District Code | |
| block_name | text | Block Name | |
| block_code | text | Block Code | |
| inst_deliveries_in_percentage | numeric | percentage of institutional deliveries in a block | |
| no_of_deliveries | numeric | number of total deliveries in a block | |
| expected_dod | numeric | expected number of deliveries in a block |
Additional Information
| Field | Value |
|---|---|
| Data last updated | November 17, 2023 |
| Metadata last updated | November 17, 2023 |
| Created | unknown |
| Format | CSV |
| License | Open Data Commons Attribution License |
| Created | 1 year ago |
| Frequency | Yearly |
| Media type | text/csv |
| Size | 8,701 |
| Additional info | Number of Blocks = 46 |
| Data extraction page | nan |
| Data insights | Exploring this dataset can offer valuable insights into the patterns and trends of deliveries in Meghalaya. Analysts can examine the variations in institutional deliveries across different blocks and assess the actual versus expected number of deliveries. Additionally, the dataset enables the identification of areas with higher or lower delivery rates, contributing to informed decision-making in healthcare planning and resource allocation. |
| Data last updated | 2,023 |
| Data retreival date | 2023-09-29 00:00:00 |
| Datastore active | True |
| District no | 11 |
| Granularity | Block |
| Has views | True |
| Id | 08b06490-3109-4b93-87dc-b04c6a466115 |
| Idp ready | True |
| Methodology | The dataset employs a systematic approach to record deliveries, capturing data on a yearly basis. The methodology involves categorizing the information based on the state, district, and block levels. Key metrics such as the percentage of institutional deliveries and the total number of deliveries are calculated for each block. The expected number of deliveries serves as a reference point for comparison. |
| No indicators | 3 |
| Package id | c089ae01-7d72-43e8-b906-d7180713be97 |
| Position | 4 |
| Sku | mothers_deliveries |
| State | active |
| States uts no | 1 |
| Url type | upload |
| Years covered | 2021-2023 |
| Methodology | The dataset employs a systematic approach to record deliveries, capturing data on a yearly basis. The methodology involves categorizing the information based on the state, district, and block levels. Key metrics such as the percentage of institutional deliveries and the total number of deliveries are calculated for each block. The expected number of deliveries serves as a reference point for comparison. |
| Similar Resources | |
| Granularity Level | Block |
| Data Extraction Page | nan |
| Data Retreival Date | 2023-09-29 00:00:00 |
| Data Last Updated | 2023 |
| Sku | mothers_deliveries |
| Dataset Frequency | |
| Years Covered | 2021-2023 |
| No of States/UT(s) | 1 |
| No of Districts | 11 |
| No of Tehsils/blocks | |
| No of Gram Panchayats | |
| Additional Information | Number of Blocks = 46 |
| Number of Indicators | 3 |
| Insights from the dataset | Exploring this dataset can offer valuable insights into the patterns and trends of deliveries in Meghalaya. Analysts can examine the variations in institutional deliveries across different blocks and assess the actual versus expected number of deliveries. Additionally, the dataset enables the identification of areas with higher or lower delivery rates, contributing to informed decision-making in healthcare planning and resource allocation. |
| IDP Ready | Yes |