If you want to master, or even just use, data analysis, Python is the place to do it. Python is easy to learn, it has vast and deep support, and most every data science library and machine learning framework out there has a Python interface.Over the last couple of months, several data science projects for Python have released new versions with major feature updates.
Some are about actual number-crunching; others make it easier for Pythonistas to write fast code optimized for those jobs.[ Tutorial: How to get started with Python. | Go deeper with the InfoWorld megaguide: The best Python frameworks and IDEs. | Keep up with hot topics in programming with InfoWorld’s App Dev Report newsletter. ]
Essential Python for data science: SciPy 1.0
What’s SciPy for
Python users who want a fast and powerful math library can use NumPy, but NumPy by itself isn’t very task-focused.
SciPy uses NumPy to provide libraries for common math- and science-oriented programming tasks, from linear algebra to statistical work to signal processing.To read this article in full or to leave a comment, please click here

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