SegoML/Generating-Data---An-Arewa-Data-Science-Project

# Mofolo Clinic Hypertension Data Analysis This project is a data generation and visualization exercise focused on understanding hypertension prevalence at Mofolo Clinic. The goal is to generate a synthetic dataset of patient records, including various chronic conditions, while emphasizing the 55-65 age group, where hypertension risk is typically higher. Key Python libraries used include: * **NumPy:** For generating numerical data and arrays. * **Pandas:** For structuring and manipulating data into DataFrames. * **Matplotlib & Seaborn:** For creating informative data visualizations like histograms, bar charts, box plots, and heatmaps. The project covers: * Simulating patient demographics and disease prevalence. * Filtering and analyzing specific populations based on age. * Visualizing key relationships and trends through various chart types. This project is designed to be a practical learning example demonstrating how to generate, manipulate, and present data effectively using Python tools. It explores ways to analyze trends and relationships within a patient dataset focused on hypertension, but also other chronic diseases.