India Phone Preference Analysis

Project Description

This Python script analyzes a dataset (india_phone_preference.csv) containing information about mobile phone preferences in India. The script processes the dataset and extracts insights based on gender, brand preference (iPhone vs. Android), payment modes, and purchase platforms.

Features

• Handles Missing Data: Fills missing values with 0.
• Gender-based Analysis:
  • Counts and calculates the percentage of male, female, and other users.
• Brand Analysis:
  • Calculates the number and percentage of iPhone and Android users.
  • Analyzes brand preference based on gender.
• Payment Mode Analysis:
  • Determines how iPhone and Android users pay (EMI, UPI, Credit Card, Debit Card, or Cash).
• Purchase Platform Analysis:
  • Identifies whether users buy online or offline.
  • Breaks down platform preference by gender.

Dependencies

Ensure you have the following Python libraries installed:

pip install numpy pandas

Usage

1. Place the india_phone_preference.csv file in the same directory as the script.
2. Run the script using:

python script.py

3. The script will output insights into the console in a tabular format.

Data Format

The india_phone_preference.csv dataset should have the following columns:

• Gender: Male, Female, Other
• Brand: iPhone, Android
• Payment Mode: EMI, UPI, Credit Card, Debit Card, Cash
• Purchase Platform: Online, Offline

Output Example

--- Gender Meta Data - Male, Females and Others ---
   Male Orders  Female Orders  Others Orders Male Percentage Female Percentage Others Percentage
0       40000         50000          10000        40.00%          50.00%         10.00%

--- Brand Meta Data Iphone or Android ---
   iPhone Orders  Android Orders iPhone Percentage Android Percentage
0         45000         55000         45.00%         55.00%