📱 Mobile Sales Data Analysis

This project performs Exploratory Data Analysis (EDA) on a mobile and laptop sales dataset using Python, Pandas, Seaborn, and Matplotlib. The goal is to extract actionable business insights from product, pricing, regional, and time-based sales data.

🔍 Key Insights:

• Top-selling brands and product types
• Regional sales performance across India
• Price distribution by RAM and ROM specs
• Monthly sales trends for demand analysis
• Correlation between price and quantity sold

📊 Visualizations Included:

10 different charts using Seaborn & Matplotlib:

• Bar plots
• Histograms
• Box plots
• Line charts
• Correlation heatmaps

🛠️ Technologies Used:

• Python
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook

📁 File

• Mobile_Sales_Analysis.ipynb – The full notebook with code, charts, and insights

📌 Author

Ahman Aspiring Data Analyst | Python & BI Enthusiast

Built With

• eda
• jupyter-notebook
• matplotlib
• numpy
• pandas
• python