Population Growth Analysis

This project analyzes population growth data from 1950 to 2023 using Python libraries such as Pandas, NumPy, Matplotlib, and Plotly.

Dataset

The dataset used in this analysis is stored in a CSV file named 'Population Growth.csv'. It contains the following columns:

• Year: The year of the population data.
• Population Growth Rate: The population growth rate for each year.
• Growth Rate: The growth rate percentage for each year.

Dependencies

To run this project, you need to have the following Python libraries installed:

• pandas
• numpy
• matplotlib
• plotly

You can install these libraries using pip:

pip install pandas numpy matplotlib plotly

Usage

1. Make sure you have the required dependencies installed.
2. Place the 'Population Growth.csv' file in the same directory as the Python script.
3. Run the Python script.

Data Analysis

The script performs the following data analysis tasks:

1. Reads the CSV file into a Pandas DataFrame.
2. Displays the first few rows of the DataFrame using head().
3. Prints information about the DataFrame using info().
4. Describes the statistical summary of the DataFrame using describe().
5. Extracts the 'Year', 'Population Growth Rate', and 'Growth Rate' columns from the DataFrame.
6. Converts the 'Population Growth Rate' column to numeric values.
7. Finds the minimum value, maximum value, and the number of data points in the 'Growth Rate' column.
8. Creates a line plot using Plotly to visualize the population growth rate over the years.
9. Creates another line plot using Plotly to visualize the growth rate percentage over the years.
10. Creates a scatter plot using Matplotlib to show the relationship between population and growth rate.
11. Customizes the x-axis ticks of the scatter plot.

Results

The script generates the following visualizations:

1. A line plot showing the population growth rate from 1950 to 2023.
2. A line plot showing the growth rate percentage from 1950 to 2023.
3. A scatter plot displaying the relationship between population and growth rate.

The script also prints the following information:

• The first few rows of the DataFrame.
• Information about the DataFrame, including column names, data types, and memory usage.
• Statistical summary of the DataFrame.
• Minimum value, maximum value, and the number of data points in the 'Growth Rate' column.

Contributing

If you would like to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with descriptive commit messages.
4. Push your changes to your forked repository.
5. Submit a pull request to the main repository.

License

This project is licensed under the MIT License.

Feel free to use and modify the code as per your requirements.

Acknowledgments

• Thanks to the developers of the Pandas, NumPy, Matplotlib, and Plotly libraries for their valuable contributions to the Python data analysis ecosystem.