Diwali_Sales_Analysis_Python

📊 This project presents an end-to-end Exploratory Data Analysis (EDA) on Diwali Sales data with the goal of uncovering actionable business insights for targeted marketing and strategic decision-making. Using Python and core data analysis libraries, the dataset is analyzed to identify key customer segments, spending behaviors, and state-wise revenue distribution during the Diwali festival season. This analysis supports real-world use cases like campaign optimization and customer profiling.

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🚀 Business Objective

Simulating the role of a junior data analyst at a retail company using Diwali sales data to:

• 🎯 Discover high-revenue customer segments
• 🧠 Recommend marketing strategies based on customer behavior
• 📈 Support business decisions using data insights

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🛠️ Tools and Technologies

Tool	Purpose
Python (Jupyter Notebook)	Analysis environment
Pandas, NumPy	Data manipulation & preprocessing
Matplotlib, Seaborn	Visualization
Power BI (optional)	Business dashboarding

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📂 Dataset Overview

• Source: Diwali Sales (fictional dataset)
• Rows: 11,251
• Columns: 15
• Features: Gender, Age Group, Marital Status, Occupation, State, Product Category, Amount, etc.

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🧹 Data Cleaning and Preprocessing

• ✔️ Removed null and missing values
• ✔️ Dropped non-relevant columns like Status, Unnamed
• ✔️ Standardized and cleaned categorical variables
• ✔️ Converted data types as required

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📊 Exploratory Data Analysis

1️⃣ Gender-based Spending

• 👩‍🦰 Females made more purchases (by count)
• 👨 Males spent more in total amount

2️⃣ Age Group Contribution

• 👥 Age group 26–35 dominates in both count and spending
• 🎯 Ideal demographic for campaign targeting

3️⃣ State-wise Performance

• 🥇 Top States: Uttar Pradesh, Maharashtra, Karnataka
• 📍 High demand zones for future campaigns

4️⃣ Marital Status Influence

• 💍 Married individuals contributed more to total revenue
• 🛍️ Family-centric spending patterns

5️⃣ Occupation vs Product Categories

• 💼 Working professionals spent the most
• 📦 Popular categories: Electronics, Clothing

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📈 Key Insights

• 🎯 Target Segment: Married Males, Aged 26–35, Working Professionals
• 🌍 Focus States: Uttar Pradesh, Maharashtra, Karnataka
• 🧾 Female customers make frequent purchases but spend less per transaction

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🔬 Conclusion & Recommendations

• ✅ Launch personalized Diwali marketing campaigns for target segments
• ✅ Focus inventory and advertising efforts in top-performing states
• ✅ Promote high-demand products based on occupational preferences

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