Routines and objects by topic#
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.
- Constants
- Array creation routines
- Array manipulation routines
- Bit-wise operations
- String functionality
- Datetime support functions
- Data type routines
- Mathematical functions with automatic domain
- Floating point error handling
- Exceptions and Warnings (
numpy.exceptions) - Discrete Fourier Transform (
numpy.fft) - Functional programming
- Input and output
- Indexing routines
- Linear algebra (
numpy.linalg) - Logic functions
- Masked array operations
- Mathematical functions
- Miscellaneous routines
- Polynomials
- Random sampling (
numpy.random) - Set routines
- Sorting, searching, and counting
- Statistics
- Test support (
numpy.testing) - Window functions