Social Network Ads Data Analysis

Overview

This project performs data analysis and visualization on a Social Network Ads dataset using Python libraries like Pandas and Matplotlib. The main objective is to explore user behavior, analyze purchasing patterns, and visualize important insights from the dataset.

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Features

• Data cleaning and preprocessing
• Exploratory Data Analysis (EDA)
• Histogram visualization
• Scatter plots and box plots
• Correlation analysis
• Customer purchase behavior analysis
• Data visualization using Matplotlib

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Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib

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Dataset

The dataset contains information about users such as:

• User ID
• Gender
• Age
• Estimated Salary
• Purchased

The analysis helps understand how factors like age and salary influence purchasing decisions.

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Project Workflow

1. Importing libraries
2. Loading dataset
3. Data cleaning
4. Data exploration
5. Data visualization
6. Insight generation

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Sample Visualizations

• Age Distribution Histogram
• Salary Distribution Plot
• Age vs Estimated Salary Scatter Plot
• Purchase Analysis Charts

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Learning Outcomes

Through this project, I learned:

• Data preprocessing techniques
• Data visualization concepts
• Exploratory Data Analysis (EDA)
• Working with Pandas DataFrames
• Creating plots using Matplotlib

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👩‍💻 Author Muskan Gupta

Connect with Me LinkedIn: linkedin.com/in/muskan-gupta-551293386

• Add Seaborn visualizations
• Build Machine Learning prediction model
• Deploy project using Streamlit

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