TheMercyOlaoluwa/Analysis-of-Health-Facilities-in-Sub-Saharan-Africa

Exploring country-level and state-level distribution, facility ownership, and facility types across health facilities in sub-Saharan Africa. # Analysis-of-Health-Facilities-in-Sub-Saharan-Africa Exploring country-level and state-level distribution, facility ownership, and facility types across health facilities in sub-Saharan Africa. ## Tools & Concepts Used - SQL - SQL Server - Data Exploration - Data Cleaning - Aggregation - CTE This dataset was compiled by Maina, J., Ouma, P.O., Macharia, P.M., et al., as part of their research titled A spatial database of health facilities managed by the public health sector in sub-Saharan Africa, published in 2019. The objective of this analysis is to explore the dataset and extract insights related to the distribution of health facilities at both the country and state (admin division) levels. It also investigates the types and ownership structures of healthcare facilities across the region. Subsequently, the analysis will narrow its focus to Nigeria to examine the state-level distribution of health facilities, as well as the ownership, facility type and healthcare service tiers within the country. ## Data Profiling The dataset contains 8 columns and 98,745 rows. There are 6 categorical variables of the varchar datatype (Country, Admin1, Facility name, Facility type, Ownership, LL Source) and 2 numerical variables: Lat (Latitude) and Long (Longitude). Ownership, Lat, Long, and LL Source contain 30,448, 2,351, 2,351, and 2,350 null values, respectively. The dataset contains 123 duplicate rows. Removing the duplicate rows leaves the row count at 98,622. ### Number of columns ``` SELECT COUNT(*) AS column_count FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'data_table'; ``` | column_count | |--------------| | 8 | ### Number of rows ``` --Number of rows SELECT COUNT(*) AS row_count FROM data_table; ``` | row_count | |-----------| | 98745 | ### columns and data types ``` SELECT column_name, data_type FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'data_table'; ``` | column_name | data_type | |------------------|-----------| | Country …