Data Analytics Journey

This repository documents my learning journey in Data Analytics using Python.

The goal is to continuously improve my skills in:

• Exploratory Data Analysis (EDA)
• Data Cleaning
• Feature Engineering
• Machine Learning
• Data Visualization
• Analytical Thinking

I am working on different dataset projects step by step to strengthen my workflow, improve my understanding of data, and build a solid foundation in Data Analytics.

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Tools & Libraries

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn
• Jupyter Notebook

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Learning Approach

This repository intentionally documents my learning process over time.

The focus is not only on final results, but also on:

• understanding datasets
• improving analytical thinking
• practicing structured workflows
• building consistency through hands-on projects
• improving technical and analytical communication

Each new project is meant to reflect gradual progress and growing experience in Data Analytics and Machine Learning.

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Repository Structure

Python_for_Data_Analysis/
│
├── 01_Titanic_Case_Study/
│   ├── 01_Titanic_EDA.ipynb
│   ├── 01b_Titanic_EDA_V2.ipynb
│   ├── 02_Titanic_FE.ipynb
│   ├── 02b_Titanic_FE_V2.ipynb
│   ├── 03_Titanic_ML.ipynb
│   ├── 03b_Titanic_ML_V2.ipynb
│   ├── Titanic_for_ML_Detailed.csv
│   ├── Titanic_for_ML.csv
│   ├── Titanic_Train.csv
│   └── README.md
├── 02_Hotel_Booking_Case_Study/
│   ├── data/
│   │   ├── hotel_bookings_ml.csv
│   │   ├── hotel_booking_no_dup_ml.csv
│   │   ├── hotel_bookings_no_dup.csv
│   │   ├── hotel_booking_with_dup_ml.csv
│   │   ├── hotel_bookings_with_dup.csv
│   │   └──  hotel_booking.csv
│   ├── notebooks/
│   │   ├── 01_Hotel_Booking_EDA.ipynb
│   │   ├── 01b_Hotel_Booking_EDA_V2.ipynb
│   │   ├── 02_Hotel_Booking_FE.ipynb
│   │   ├── 02b_Hotel_Booking_FE_V2.ipynb
│   │   ├── 03_Hotel_Booking_ML.ipynb
│   │   └── 03b_Hotel_Booking_ML_V2.ipynb
│   ├── picture/
│   │   ├── Booking_Analysis_Dashbaord.png
│   │   └── Cancellation_Analysis_Dashboard.png
│   ├── HotelBookingReport.pdf
├── 03_Superstore_Case_Study/
│   ├── data/
│   │   └── superstore.csv
│   ├── notebooks/
│   │   ├── 01_Superstore_EDA.ipynb
│   │   └── 04_Superstore_SQL.ipynb
│
├── More projects comming...
│
└── README.md