data_visualization_with_pandas_library

Deep Analysis of "Billionaires Statistics Dataset (2023)" which was uploaded by NIDULA ELGIRIYEWITHANA on Kaggle.com

Billionaires Statistics Analysis

This Python script is designed to perform data analysis and visualization on a dataset containing information about billionaires. The script offers insights into the distribution of billionaires across industries, gender, countries, and whether they are self-made. Additionally, it calculates statistics related to the age and final worth of billionaires.

Usage

1. Clone or Download the Repository:

   You can clone this repository to your local machine using Git, or you can simply download it as a ZIP file. Here's how you can clone it:

   git clone https://github.com/yourusername/billionaires-stats.git

Install Required Python Libraries:

Make sure you have the necessary Python libraries installed. You can install them using pip: bash

• Copy code: pip install pandas numpy matplotlib
• Replace the Data File:
• Replace the sample data file (/YourFilePath/Billionaires Statistics Dataset.csv) with your own dataset. You can specify the path to your data file in the load_data function within the script.
• Run the Script:
• Execute the script to generate visualizations and statistics:
• Copy code: python billionaires_stats.py
• This will create and save plots and display statistics.

Functions

The script includes the following functions:

• load_data(file_path): Loads data from a CSV file and returns it as a Pandas DataFrame.
• plot_industry_distribution(data): Generates a plot showing the distribution of billionaires across different industries.
• plot_gender_distribution(data): Creates a pie chart illustrating the gender distribution of billionaires.
• plot_country_distribution(data): Produces bar charts displaying the distribution of billionaires by country. The data is split into * three parts for clarity.
• plot_selfmade_distribution(data): Generates a pie chart showing the ratio of self-made billionaires compared to those who are not self-made.
• calculate_statistics(data): Calculates and prints statistics on the age and final worth of billionaires, including median, mean, mode, and standard deviation.

Results

The script will generate the following output:

• Industry Distribution Plot: A bar chart showing the distribution of billionaires across different industries. This plot will be saved as industry_distribution.png.
• Gender Distribution Plot: A pie chart illustrating the gender distribution of billionaires. This plot will be saved as gender_distribution.png.
• Country Distribution Plots: A set of bar charts displaying the distribution of billionaires by country. The data is split into three parts for clarity. These plots will be saved as country_distribution.png.
• Self-Made Distribution Plot: A pie chart showing the ratio of self-made billionaires compared to those who are not self-made. This plot will be saved as selfmade_distribution.png.
• Statistics: The script will calculate and print statistics on the age and final worth of billionaires, including the median, mean, mode, and standard deviation.