Introduction: The Patient Health Data Analysis and Recommendation Reporting System is designed to analyze patient health data and provide recommendations based on the analysis. It leverages various analytical techniques to derive insights from the data and generate personalized recommendations for healthcare professionals and patients.
Project Overview: Data exploration and preprocessing Answering a variety of questions related to global and country-specific COVID-19 data analysis Calculations and visualizations to address specific queries regarding COVID-19 cases, recoveries, deaths, and trends over time Utilization of Python libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization
Questions Answered The notebook addresses a wide range of questions related to COVID-19 data analysis, including:
Total number of confirmed cases globally Number of countries included in the dataset Country with the highest number of confirmed cases Average number of deaths per day globally Number of cases reported in a specific country on a particular date Total number of recovered cases globally Number of active cases in a specific country on a particular date Country with the highest number of deaths Overall mortality rate globally And many more...
Dependencies: Python 3, Jupyter Notebook, Pandas, NumPy, Matplotlib.