Demographic-Data_Analyzer

Demographic Data Analysis

This repository contains a Python script for analyzing demographic data using Python and Pandas.

Usage

1. Clone the repository or download the files to your local machine.

2. Ensure you have Python installed.

3. Install the necessary dependencies:

   pip install pandas

4. Run the main.py script to test the calculate_demographic_data function:

   python main.py

Demographic Data Analysis

The calculate_demographic_data Python script performs demographic analysis on a dataset containing information about individuals. The analysis includes computations related to race representation, education levels, salaries, and more.

Function Details

The calculate_demographic_data function conducts the following tasks:

• Reads the dataset file adult.data.csv.
• Analyzes demographic data, such as race representation, education levels, average age of men, minimum work hours, and percentages across various demographics.
• Identifies the country with the highest percentage of individuals earning over 50K.
• Determines the most popular occupation among individuals earning over 50K in India.

Output

The function returns a dictionary containing the following demographic data:

• race_count: Number of individuals from each race.
• average_age_men: Average age of men.
• percentage_bachelors: Percentage of individuals with a Bachelor's degree.
• higher_education_rich: Percentage of individuals with advanced education earning over 50K.
• lower_education_rich: Percentage of individuals without advanced education earning over 50K.
• min_work_hours: Minimum number of work hours per week.
• rich_percentage: Percentage of individuals earning over 50K among those working the minimum hours.
• highest_earning_country: Country with the highest percentage of individuals earning over 50K.
• highest_earning_country_percentage: Highest percentage of individuals earning over 50K in a country.
• top_IN_occupation: Most popular occupation among individuals earning over 50K in India.

Note

Ensure the dataset file adult.data.csv is correctly formatted and placed in the script's directory before running the analysis.