Nearly every scientist working in Python draws on the power of NumPy. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to …

The reference guide contains a detailed description of the functions, modules, and objects included in NumPy. The reference describes how the methods work and which parameters …

The only prerequisite for installing NumPy is Python itself. If you don’t have Python yet and want the simplest way to get started, we recommend you use the Anaconda Distribution - it includes …

The NumPy library contains multidimensional array data structures, such as the homogeneous, N-dimensional ndarray, and a large library of functions that operate efficiently on these data …

NumPy’s main object is the homogeneous multidimensional array. It is a table of elements (usually numbers), all of the same type, indexed by a tuple of non-negative integers.

What is NumPy? # NumPy is the fundamental package for scientific computing in Python.

NumPy reference Routines and objects by topic Mathematical functions numpy.power

numpy.where # numpy.where(condition, [x, y, ]/) # Return elements chosen from x or y depending on condition.

Notes NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not …

The matmul function implements the semantics of the @ operator defined in PEP 465. It uses an optimized BLAS library when possible (see numpy.linalg). Examples Try it in your browser! For …