🐍 Python Data Analysis & Machine Learning Projects Pandas | Jupyter Notebook | Scikit-learn | Data Mining | EDA

Hello Connections! 👋 I'm Shaif Khan, a data analyst and backend developer with an MCA from Lalit Narayan Mishra Institute of Economic Development and Social Change, Patna, Bihar, affiliated to Aryabhatta Knowledge University, Patna, Bihar.

Here’s a collection of my Python-based projects, where I performed data cleaning, EDA, predictive modeling, and association rule mining — all using Jupyter Notebook, Pandas, and Scikit-learn for real-world business insights.

🧾 Project Highlights:

🏦 Loan Approval Prediction (ML Project) ✅ Cleaned and preprocessed loan application data

  ✅ Performed EDA: correlations, missing values, feature engineering
  
  ✅ Built and evaluated ML classification models to predict loan approval
  
  ✅ Tools used: Pandas, Matplotlib, Scikit-learn, Seaborn

🪔 Diwali Sales Data Analysis (Pandas Project) ✅ Loaded and cleaned retail data from Diwali season

  ✅ Performed sales trend analysis, customer behavior segmentation
  
  ✅ Delivered actionable marketing insights using Pandas + Visualization
  
  ✅ Designed in Jupyter Notebook with clean and visual output

📞 Customer Churn & Telecom EDA ✅ Performed detailed EDA on telecom customer data

  ✅ Analyzed churn patterns, customer retention KPIs
  
  ✅ Visualized findings using Matplotlib and Seaborn
  
  ✅ Preprocessed data for potential ML models

🛒 Market Basket Analysis (MBA) ✅ Implemented Apriori Algorithm using mlxtend

  ✅ Cleaned and reshaped retail transaction data for analysis
  
  ✅ Discovered frequent itemsets and generated association rules
  
  ✅ A great example of data mining and recommendation system foundations

🔧 Skills & Tools Used: 🐼 Pandas – Data cleaning, manipulation, and exploration

  📊 Matplotlib & Seaborn – For visual storytelling
  
  🔍 Scikit-learn – For building ML models
  
  🧠 Apriori Algorithm (mlxtend) – For association rule mining
  
  📓 Jupyter Notebook – Documentation, EDA, model training
  
  🔗 Merge, Join, Concatenate – Handling multiple datasets

🎯 What These Projects Demonstrate: 🧹 Proficiency in data wrangling and merging

  🔍 Strong EDA & data storytelling skills
  
  🤖 Experience in machine learning model building & evaluation
  
  🧠 Understanding of customer behavior & recommendation logic
  
  🧑‍💻 Practical, industry-relevant analytics in Python

🔗 Let’s Connect! Want to explore notebooks, models, or discuss use cases? Feel free to reach out — I’d love to collaborate or showcase more!

📌 Tags & Topics #Python #Pandas #EDA #JupyterNotebook #MachineLearning #LoanPrediction #DiwaliSales #CustomerChurn #MarketBasketAnalysis #AprioriAlgorithm #DataMining #ScikitLearn #RetailAnalytics #DataVisualization