Python libraries : Select the best for data science

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Python libraries : Select the best for data science

Always a selection of useful and best libraries for our goals can be so effective. About data science, the most important Python libraries for data science tasks covering areas: data mining, data processing, modeling, and visualization are:

Read more: What is Data Science? The accelerator approach to solving your problem!

Python libraries for Data Mining or Data discovery

Data mining

1. Scrapy

Scrapy is a free and open-source web-crawling framework written in Python. Originally designed for web scraping, it can also be used to extract data using APIs or as a general-purpose web crawler.

2. BeautifulSoup

Beautiful Soup is a Python package for parsing HTML and XML documents. It creates a parse tree for parsed pages that can be used to extract data from HTML, which is useful for web scraping.

Python libraries for Data Processing and Statistics Modeling

For Data Processing and  Statistics Modeling

3. NumPy

NumPy (Numerical Python) is a perfect tool for scientific computing and performing basic and advanced array operations.

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

Know more: Numpy : The linear algebra library in Python for data science

4. SciPy

SciPy is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers, and other tasks common in science and engineering.

5. Pandas

pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license.

6. Keras

Keras is an open-source library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library. Up until version 2.3 Keras supported multiple backends, including TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML.

7. SciKit-Learn

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression, and clustering algorithms including support vector machines, …

8. PyTorch

PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook’s AI Research lab. It is free and open-source software released under the Modified BSD license.

9. TensorFlow

TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library and is also used for machine learning applications such as neural networks.

10. XGBoost

XGBoost is an open-source software library that provides a gradient boosting framework for C++, Java, Python, R, Julia, Perl, and Scala. It works on Linux, Windows, and macOS. From the project description, it aims to provide a “Scalable, Portable and Distributed Gradient Boosting Library”.

Python libraries for Data Visualization

Data Visualization

11. Matplotlib

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.

12. Seaborn

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

13. Bokeh

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords …

14. Plotly

plotly.py is an interactive, open-source, and browser-based graphing library for Python

15. pydot

This library helps to generate oriented and non-oriented graphs. It serves as an interface to Graphviz (written in pure Python). You can easily show the str ucture of graphs with the help of this library. That comes in handy when you’re developing algorithms based on neural networks and decision trees.

Conclusion

There are many other tools that can be helpful for data science work. These libraries are essential for building high-performing ML models in Python.

Python → Libraries → Modules

 

References:

  1. www.dataquest.io
  2. www.en.wikipedia.org
By |2020-11-08T14:16:47+03:3022nd October, 2020|Categories: DS knowledge, Python knowledge|Tags: , , |0 Comments

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