Python for Data Scientists - SciPy
Introduction This article continues the Python for Data Scientists series by talking about SciPy . It is built on top of NumPy, of which we've already talked in the previous article . SciPy provides many user-friendly and efficient numerical routines addressing a number of different standard problem domains in scientific computing such as integration, differential and sparse linear system solvers, optimizers and root finding algorithms, Fourier Transforms, various standard continuous and discrete probability distributions and many more. Together NumPy and SciPy form a reasonably complete computational replacement for much of MATLAB along with some of its add-on toolboxes. Installation Installation of SciPy is trivial. In many cases, it will be already supplied to you with python distribution, or as usual may be installed manually using python package manager pip install scipy Depending on the running OS, you might be needing to install gfortran , prior to SciPy ins