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🐍 Hands-on Python & Data Science resources β€” statistics, pandas, regex, machine learning projects, cheat sheets, and practice notebooks.

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SheemaMasood381/Python-For-DataScience

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Python For DataScience

Welcome to the Python For DataScience repository! This repository is a comprehensive collection of Python resources, including Jupyter notebooks and Word documents, that cover fundamental concepts, hands-on exercises, and advanced topics in Python programming and data science.

Repository Structure

1. Python Notes in IPYNB Format
     - Fundamental Concepts in Statistics: In-depth exploration of statistical concepts relevant to data science.
     - Pandas: Notebooks covering data manipulation and analysis using the Pandas library.
     - Regular Expressions: Learn to use regular expressions for pattern matching in Python.
     - Loops, Functions, & Classes: Comprehensive coverage of control structures, functions, and object-oriented programming in Python.
     - Practice Notes: Hands-on practice notebooks for key Python concepts.
     
2. Python Notes in Word Format
     - Data Types, Functions, and More: Documents detailing Python's data types, functions, and key libraries like Pandas.
     - Statistical Concepts: A deep dive into statistics, including probability distributions and fundamental statistical methods.
     - Cheat Sheets and Reference Material: Quick reference PDFs for regular expressions, Python functions, and more.
     
3. Regular Expressions
     - A focused directory with notebooks and cheat sheets dedicated to mastering regular expressions in Python.
     
4. Projects
     - Data Cleaning Practice: Hands-on practice with data cleaning techniques.
     - Final Projects: Real-world data science projects, including an analysis of New York job postings.

Getting Started

To start using the materials in this repository:

Clone the repository:

- git clone https://github.com/SheemaMasood381/Python-For-DataScience.git

Navigate through the directories to explore the notebooks and documents. For Jupyter notebooks, ensure you have Jupyter installed and run them locally.

Contributions

Feel free to contribute to this repository by creating pull requests, reporting issues, or suggesting new topics and improvements.

License

This repository is open-sourced under the MIT License.

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🐍 Hands-on Python & Data Science resources β€” statistics, pandas, regex, machine learning projects, cheat sheets, and practice notebooks.

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