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 TABcompletion 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 greaterthan signs:
>>> x = 42 >>> x = x + 1
Use the builtin 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.
To search for documents containing a keyword, do:
>>> np.lookfor('keyword') ... # doctest: +SKIP
Generalpurpose documents like a glossary and help on the basic concepts of numpy are available under the doc submodule:
>>> from numpy import doc >>> help(doc) ... # doctest: +SKIP
numpy.dual
is deprecated. Use the functions from NumPy or Scipy
directly instead of importing them from numpy.dual
.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).
Most of the functions in numpy
return a copy of the array argument
(e.g., np.sort
). Inplace 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 subpackage 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 subnamespace 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 
Subpackage containing the matrix class and related functions. 
Module  setup 
Undocumented 
Package  tests 
No package docstring; 3/8 modules documented 
Module  version 
Undocumented 
From __init__.py
:
Constant  __NUMPY_SETUP__ 
Undocumented 