https://github.com/satyamgupta53/python-collections

Well-structured repository to make direct references to Python programs including File IO, Exceptional Handling, Virtual Env, Data Analysis, OOPS, Multi-Threading, Memory Management.
https://github.com/satyamgupta53/python-collections

exception-handling file-handling multithreading oops-in-python python3

Last synced: 27 days ago
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Well-structured repository to make direct references to Python programs including File IO, Exceptional Handling, Virtual Env, Data Analysis, OOPS, Multi-Threading, Memory Management.

• Host: GitHub
• URL: https://github.com/satyamgupta53/python-collections
• Owner: satyamgupta53
• Created: 2024-04-24T19:19:30.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2025-01-09T05:46:47.000Z (about 1 month ago)
• Last Synced: 2025-01-09T06:42:18.589Z (about 1 month ago)
• Topics: exception-handling, file-handling, multithreading, oops-in-python, python3
• Language: Jupyter Notebook
• Homepage:
• Size: 290 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Python Collections

Welcome to this comprehensive repository for your Python Programming adventures! Here, you'll find a treasure trove of programs and interactive Jupyter Notebooks designed to equip you with the skills to tackle real-world problems.

This repository caters to both beginners and experienced practitioners:

New to ML & NLP? Our notebooks guide you step-by-step through core concepts, providing a solid foundation for your journey.

Ready to dive deeper? Explore Python programs tackling various ML and NLP tasks, offering a springboard for your own projects.

What awaits you:

Python Programs: Practical code examples covering different aspects of DSA & OOPS.

Jupyter Notebooks: Interactive tutorials for a hands-on learning experience.

Emphasis on Clarity: Well-documented code and explanations for easy understanding.

Feel free to explore, experiment, and contribute! We encourage you to adapt these resources for your specific goals and build upon the collective knowledge within this repository. Let's unlock the power of ML and NLP together!

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install any of the required libraries in your computer system.

```bash

pip install _______

```

## Usage

```python

pip install pandas

# read a csv file

data = pandas.read_csv(file_path, sep=",")

# print top 5 rows

data.head()

```

## Contributing

Pull requests are welcome. For major changes, please open an issue first

to discuss what you would like to change.