I'm actively learning Data Science with a focus on practical, real-world application. This repo documents my progress from mastering core Pandas & NumPy operations to building complete data projects. Everything here is written, tested, and understood by me.
Data Science/
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├── Basics/ # Core concepts, learned hands-on with real data
│ ├── players_20.csv # Football player Dataset
│ ├── StudentsPerformance.csv # Dataset Student performace
│ ├── laptop_price.csv # Dataset laptop information and prices
│ |── AttrMethFunc.ipynb # Attributes, methods & functions
│ ├── CreateDataFrame.ipynb # Building & structuring DataFrames using Numpy and Pandas
│ ├── ColBasedCondition.ipynb # Column based filtering using conditon / creating codititional columns, using numpy select/where function
│ ├── DataInDict.ipynb # Adding multiple dataframes to dict for better & easy access
│ ├── Duplicate.ipynb # Mutiple methods to manipluate data using duplicated/drop_duplicate function
│ ├── Extraction.ipynb # Extractig data and manipluate using loc and iloc
│ ├── FilteringDataMethods.ipynb # Filtering data using only pandas methods
│ ├── Index.ipynb # Indexing
│ ├── isin.ipynb # using isin function to analayes data with conditons/values
│ ├── Operations.ipynb # Arithmetic & logical operations
│ ├── Queries.ipynb # Using query fucntion and dtype to fetch and change data type
│ ├── Rename.ipynb # Renaming columns & indexes
│ ├── SortValues.ipynb # Sorting data
│ └── ValueCount.ipynb # Frequency analysis
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└── Projects/ # Applied projects on real datasets
└── WebScraping.ipynb # Scraping multiple dataset[football(season and leagues)] from web using URL patterns & loops
- Python
- Pandas
- NumPy
- Jupyter Notebooks
This repository is part of my long-term path toward becoming proficient in Data Science and Machine Learning. I learn by doing every notebook here uses real data and solves real problems. Much more to come.
For educational purposes only.