merna599/covid19-egypt-analysis

COVID-19 data analysis in Egypt using Python and visualizations # covid19-egypt-analysis COVID-19 data analysis in Egypt using Python and visualizations 📊 COVID-19 Egypt Data Analysis This project analyzes the spread of COVID-19 in Egypt using publicly available data from Our World in Data. It includes visualizations and trends to understand the impact and progression of the virus in Egypt, with a comparison to China. ## 🎯 Objective - Track daily and total COVID-19 cases in Egypt. - Analyze monthly death trends. - Calculate the death rate (deaths as a percentage of cases). - Use 3-month moving averages to visualize trends. - Compare Egypt's situation to China. - Create clear visualizations using Matplotlib and Plotly. ## 📁 Dataset - Source: Our World in Data – COVID-19 - The dataset includes case numbers, deaths, testing, and more for countries around the world. ## 🛠️ Tools & Libraries - Python - Pandas - Matplotlib - Seaborn - Plotly - Google Colab ## 🔍 Key Insights - Egypt saw the highest number of deaths during [Month, Year] 📌. - The death rate fluctuated but generally followed the trend of new cases. - Compared to China, Egypt had different peaks in case numbers and smoother recovery periods. - Using 3-month averages helped uncover more stable trends in both cases and deaths. ## 📌 How to Run 1. Open the `.ipynb` file in Google Colab or Jupyter Notebook. 2. Run the cells in order. 3. Visualizations will be generated for each section. ## 🔗 Project Link 👉 View the Notebook on GitHub