package documentation

  1. 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, 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 function does.

To search for documents containing a keyword, do:

>>> np.lookfor('keyword')
... # doctest: +SKIP

General-purpose documents like a glossary and help on the basic concepts of numpy are available under the doc sub-module:

>>> from numpy import doc
>>> help(doc)
... # doctest: +SKIP

Available subpackages

Topical documentation on broadcasting, indexing, etc.
Basic functions used by several sub-packages.
Core Random Tools
Core Linear Algebra Tools
Core FFT routines
Polynomial tools
NumPy testing tools
Fortran to Python Interface Generator.
Enhancements to distutils with support for Fortran compilers support and more.


Run numpy unittests
Show numpy build configuration
Overwrite certain functions with high-performance SciPy tools. Note: numpy.dual is deprecated. Use the functions from NumPy or Scipy directly instead of importing them from numpy.dual.
Make everything matrices.
NumPy version string

Viewing documentation using IPython

Start IPython with the NumPy profile (ipython -p numpy), which will import numpy under the alias np. Then, use the cpaste command to paste examples into the shell. To see which functions are available in numpy, type np.<TAB> (where <TAB> refers to the TAB key), or use np.*cos*?<ENTER> (where <ENTER> refers to the ENTER key) to narrow down the list. To view the docstring for a function, use np.cos?<ENTER> (to view the docstring) and np.cos??<ENTER> (to view the source code).

Copies vs. in-place operation

Most of the functions in numpy return a copy of the array argument (e.g., np.sort). In-place versions of these functions are often available as array methods, i.e. x = np.array([1,2,3]); x.sort(). Exceptions to this rule are documented.

Module ctypeslib ============================ ctypes Utility Functions ============================
Package distutils An enhanced distutils, providing support for Fortran compilers, for BLAS, LAPACK and other common libraries for numerical computing, and more.
Module dual
Deprecated since version 1.20.
Package f2py Fortran to Python Interface Generator.
Package fft Discrete Fourier Transform (numpy.fft) =============================================
Package lib Note: almost all functions in the numpy.lib namespace are also present in the main numpy namespace. Please use the functions as np.<funcname> where possible.
Package linalg numpy.linalg ================
Package ma ============= Masked Arrays =============
Module matlib No module docstring; 8/8 functions documented
Package polynomial A sub-package for efficiently dealing with polynomials.
Package random ======================== Random Number Generation ========================
Package testing Common test support for all numpy test scripts.
Package typing ============================ Typing (numpy.typing) ============================
Module ​_distributor​_init Distributor init file
Module ​_globals Module defining global singleton classes.
Module ​_pytesttester Pytest test running.
Module ​_version Undocumented
Package array​_api A NumPy sub-namespace that conforms to the Python array API standard.
Package compat Compatibility module.
Module conftest Pytest configuration and fixtures for the Numpy test suite.
Package core Contains the core of NumPy: ndarray, ufuncs, dtypes, etc.
Package doc No package docstring; 0/2 variable, 2/2 modules documented
Package matrixlib Sub-package containing the matrix class and related functions.
Module setup Undocumented
Package tests No package docstring; 3/8 modules documented
Module version Undocumented


Constant __NUMPY​_SETUP__ Undocumented
__NUMPY_SETUP__: bool =