For data science and machine learning, it makes sense because the most popular packages are all in Python at this moment (strictly speaking, they have interfaces in Python but the underlying native code is in C++).
For academics who do data analysis and scientific computing, the last few years have seen an explosion of scientific packages available in Python. The major packages, NumPy/SciPy/matplotlib/pandas, also become more feature-complete to the point that one can do everything that is used to be done in MATLAB now in this set of packages. That's free MATLAB with better performance and more potential for optimization. No wonder people are switching to the Python ecosystem.
For data science and machine learning, it makes sense because the most popular packages are all in Python at this moment (strictly speaking, they have interfaces in Python but the underlying native code is in C++).
For academics who do data analysis and scientific computing, the last few years have seen an explosion of scientific packages available in Python. The major packages, NumPy/SciPy/matplotlib/pandas, also become more feature-complete to the point that one can do everything that is used to be done in MATLAB now in this set of packages. That's free MATLAB with better performance and more potential for optimization. No wonder people are switching to the Python ecosystem.
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