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NumPy: Made for scientific computations, included with Anaconda, provides an abundance of useful features for operations on n-arrays and matrices in Python, it also provides vectorization of mathematical operations on the NumPy array type, which improves performance and speeds up the execution of the script.
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SciPy: For engineering and science, has built-in functions for numerical integration, optimization of algorithms, it uses a lot of NumPy arrays.
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Pandas: Used to work with larges amounts of data in a simple and intuitive manner. These 3 libraries are the basic stack for a data scientist.
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Matplotlib: For data visualization it has a lot of plot functions like line and scatter plots, bar charts, histograms.
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Seaborn: Mostly used in visualization of statistical models, based in Matplotlib and higly dependent on that.
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SciKit-Learn: Includes functions for machine learning, and image processing
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NLTK: The name stands for Natural Language Toolkit, and is used for Linguistics, and Cognitive Science Artificial Intelligencce.
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Django: High level web framework, fast, secure, and scalable, webapps like Instagram, Pinterest or Quora are built using Django.
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Astropy: Software packages designed for astronomy and astrophysics.
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Pygame: Set of Python modules oriented to 2D game programming but you con also use for creating GUI's (Graphic User Interfaces), or multimedia software.
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Pillow: Python Imaging Library for image processing (convert images, cutting and merging images, geometrical transformations, color transformations, etc).
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OpenCV: Open Source Computer Vision Library, supports C, C++, Java and Python for PC, Android or iOS applications, you can check some examples here.
- Examples of the most used Python Libraries
- NumPy Documentation
- SciPy Documentation
- Pandas Documentation
- Matplotlib Documentation
- Seaborn Documentation
- SciKit-Learn Documentation
- NLTK Documentation
- Astropy Documentation
- Django Documentation
- Pygame Documentation
- Pillow Documentation
- OpenCV official page