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Welcome to Python Path

This repository provides a collection of Jupyter notebooks utilizing NumPy, Pandas, and other essential Python notebooks for data analysis and manipulation. It's designed to be a valuable resource for anyone interested in learning and applying these powerful tools.

Getting Started: Prerequisites: Ensure you have Python (version 3.x recommended) and Jupyter Notebook installed on your system. You can download them from the official websites: Python: https://www.python.org/downloads/ Jupyter Notebook: https://jupyter.org/install

Clone the Repository: Use Git to clone this repository to your local machine:

git clone https://github.com/lala2398/Python_path.git

Launch Jupyter Notebook: Navigate to the cloned repository directory using your terminal and launch Jupyter Notebook:

cd [repository-name]
jupyter notebook

This will open a web interface where you can browse and execute the notebooks within this repository.

Using the Notebooks: Open the desired notebook in the Jupyter Notebook interface. Each notebook is designed to be self-contained, with clear explanations and code examples. Feel free to experiment with the code, modify it to fit your specific needs, and explore different functionalities.

Additional Notes: The data folder may contain various file formats (e.g., CSV, Excel).

Data

Notebooks from Other courses

Beyond the NumPy and Pandas notebooks, explore notebooks from other courses included in this repository :

Python 101 IBM

IBM Data Analysis with Python

Projects

Dive deeper into my data analysis journey with these projects :

Gamboo Projects : Python tasks for Data Analysis Tasks

Contribution:

Welcome contributions to this repository! If you have any helpful notebooks or data analysis examples to share, feel free to submit a pull request.

License:

This repository is licensed under MIT License. You can find the license details in the LICENSE file.

We hope this repository empowers you to explore the exciting world of data analysis with NumPy, Pandas, and other powerful Python libraries!

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