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An array object of arbitrary homogeneous items 2. Fast mathematical operations over arrays 3. Linear Algebra, Fourier Transforms, Random Number Generation How to use the documentation ---------------------------- Documentation is available in two forms: docstrings provided with the code, and a loose standing reference guide, available from `the NumPy homepage `_. We recommend exploring the docstrings using `IPython `_, an advanced Python shell with TAB-completion and introspection capabilities. See below for further instructions. The docstring examples assume that `numpy` has been imported as ``np``:: >>> import numpy as np Code snippets are indicated by three greater-than signs:: >>> x = 42 >>> x = x + 1 Use the built-in ``help`` function to view a function's docstring:: >>> help(np.sort) ... # doctest: +SKIP For some objects, ``np.info(obj)`` may provide additional help. This is particularly true if you see the line "Help on ufunc object:" at the top of the help() page. Ufuncs are implemented in C, not Python, for speed. The native Python help() does not know how to view their help, but our np.info() function does. Available subpackages --------------------- lib Basic functions used by several sub-packages. random Core Random Tools linalg Core Linear Algebra Tools fft Core FFT routines polynomial Polynomial tools testing NumPy testing tools distutils Enhancements to distutils with support for Fortran compilers support and more (for Python <= 3.11) Utilities --------- test Run numpy unittests show_config Show numpy build configuration __version__ NumPy version string Viewing documentation using IPython ----------------------------------- Start IPython and import `numpy` usually under the alias ``np``: `import numpy as np`. Then, directly past or use the ``%cpaste`` magic to paste examples into the shell. 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