RoutinesΒΆ
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
- Discrete Fourier Transform (
numpy.fft
) - 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
) - Miscellaneous routines
- Padding Arrays
- Polynomials
- Random sampling (
numpy.random
) - Set routines
- Sorting, searching, and counting
- Statistics
- Test Support (
numpy.testing
) - Window functions