Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/kanika300393/python_libraries_ds

This repository is a curated collection of Python libraries designed specifically for Data Science enthusiasts. Whether you're a beginner just getting started or an experienced data scientist looking to expand your toolkit, you'll find a range of libraries here that cater to various aspects of Data Science.
https://github.com/kanika300393/python_libraries_ds

Last synced: 10 days ago
JSON representation

This repository is a curated collection of Python libraries designed specifically for Data Science enthusiasts. Whether you're a beginner just getting started or an experienced data scientist looking to expand your toolkit, you'll find a range of libraries here that cater to various aspects of Data Science.

Awesome Lists containing this project

README 

        
# Python_Libraries_DS



![image](https://github.com/user-attachments/assets/db9ddd05-cdae-4c20-82a0-c115c051f20d)



 

This repository is a curated collection of Python libraries designed specifically for Data Science enthusiasts. Whether you're a beginner just getting started or an experienced data scientist looking to expand your toolkit, you'll find a range of libraries here that cater to various aspects of Data Science.



# Why This Repository?

The world of Data Science is vast, and the tools available are constantly evolving. This repository aims to provide a comprehensive, up-to-date collection of libraries that can help you stay at the cutting edge of the field. Each library included here has been selected for its relevance, utility, and ease of use, ensuring that you have the best tools at your disposal as you work on your Data Science projects.



# What's Inside?

You'll find libraries organized by category, with clear explanations of their functionality and examples of how to use them. Whether you're looking for libraries to help with data cleaning, model building, or data visualization, this repository has got you covered.



# Getting Started: Key Libraries for Data Science



For those new to Data Science, getting started can be overwhelming due to the abundance of tools and libraries available. Here are some of the essential Python libraries that every Data Science student should familiarize themselves with:



### Pandas:



The go-to library for data manipulation and analysis. Pandas makes it easy to handle structured data and perform operations such as merging, filtering, and grouping data.



### NumPy: 

A fundamental package for scientific computing in Python. It provides support for arrays, matrices, and many mathematical functions.



### Matplotlib & Seaborn: 

These libraries are essential for data visualization. Matplotlib provides the basic framework for creating static, animated, and interactive plots, while Seaborn builds on Matplotlib to offer more aesthetically pleasing and informative visualizations.



### Scikit-learn: 

A key library for machine learning, providing simple and efficient tools for data mining and data analysis. It includes various algorithms for classification, regression, clustering, and more.



### TensorFlow & PyTorch: 

For those venturing into deep learning, TensorFlow and PyTorch are the leading libraries. They offer powerful tools to build and train complex neural networks.