This project aims to analyze and explore data related to healthcare facilities, including bed capacities and business information. The analysis involves data cleaning, summary statistics, and outlier detection.
The following R libraries are used for data manipulation, visualization, and database interaction:
- dplyr
- tidyr
- tibble
- ggplot2
- DBI
- RSQLite
The project starts by loading three data tables:
bed_fact_tab: Facts about bed capacities in healthcare facilities.bed_type_tab: Information about bed types in healthcare facilities.business_tab: Business-related data for healthcare facilities.
Summary statistics are generated for each data table to understand the data distribution and characteristics.
Outliers in the bed_fact_tab table are identified using boxplots and the interquartile range (IQR) method. Outliers are removed from the columns license_beds, census_beds, and staffed_beds.
Rows containing NA values after outlier removal are dropped to ensure data integrity.
Boxplots are generated to visualize the distribution of bed capacities (license_beds, census_beds, staffed_beds) after outlier removal.
- Requirements: Ensure you have R installed on your system.
- Setup Environment: Install the required libraries listed in the "Libraries Used" section.
- Run the Code: Execute the R script to load the data, perform analysis, and visualize the results.