Routines¶
In this chapter routine docstrings are presented, grouped by functionality. Many docstrings contain example code, which demonstrates basic usage of the routine. The examples assume that NumPy is imported with:
>>> import numpy as np
A convenient way to execute examples is the %doctest_mode mode of IPython, which allows for pasting of multi-line examples and preserves indentation.
- Array creation routines
- Array manipulation routines
- Binary operations
- String operations
- C-Types Foreign Function Interface (numpy.ctypeslib)
- Datetime Support Functions
- Data type routines
- Optionally Scipy-accelerated routines (numpy.dual)
- Mathematical functions with automatic domain (numpy.emath)
- Floating point error handling
- Financial functions
- Functional programming
- Numpy-specific help functions
- Indexing routines
- Input and output
- Linear algebra (numpy.linalg)
- Logic functions
- Masked array operations
- Mathematical functions
- Matrix library (numpy.matlib)
- Numarray compatibility (numpy.numarray)
- Old Numeric compatibility (numpy.oldnumeric)
- Miscellaneous routines
- Padding Arrays
- Polynomials
- Random sampling (numpy.random)
- Set routines
- Sorting, searching, and counting
- Statistics
- Test Support (numpy.testing)
- Asserts
- Window functions