This Python script performs data analysis and visualization of COVID-19 data in Brazil using various libraries, including Pandas, Geopandas, Matplotlib, Squarify, and Seaborn. The script generates data-driven graphs and figures to analyze the COVID-19 situation in Brazil. The script was written by @diguitarrista for demonstration purposes and is not intended for commercial or academic use.

Before running the script, make sure you have the following libraries installed:

• Pandas
• Geopandas
• Matplotlib
• Squarify
• Seaborn

You can install these libraries using pip:

pip install pandas geopandas matplotlib squarify seaborn

1. Clone this repository or download the script to your local machine.

2. Ensure you have the required COVID-19 data source in a compatible format (e.g., CSV, GeoJSON). You will need to load this data into the script.

3. Open the script in your preferred Python environment (e.g., Jupyter Notebook, Visual Studio Code).

4. Customize the script to load and analyze your specific COVID-19 dataset. This may involve modifying data loading, manipulation, and visualization steps.

5. Execute the script to generate data-driven graphs and figures based on your dataset.

6. Review the generated visualizations and analysis to gain insights into the COVID-19 situation in Brazil.

• Importing Libraries: The script begins by importing the necessary Python libraries for data analysis and visualization.

• Data Loading: This section is where you should load your COVID-19 dataset. Ensure that the data is correctly formatted and accessible.

• Data Manipulation and Analysis: Customize this part of the script to perform specific data manipulation and analysis tasks on your dataset.

• Data Visualization: Use Matplotlib, Squarify, and Seaborn to create data visualizations, such as graphs and figures, based on your dataset.

• Output and Display: This script may require additional code to display or save the generated plots. You can adapt this section as needed.

Feel free to contribute to the script by improving its functionality or adding more data visualization features. You can submit pull requests to the repository to share your enhancements with the community.

Data Source: https://github.com/wcota/covid19br/blob/master/cases-brazil-cities.csv