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Routines
ΒΆ
Array creation routines
Ones and zeros
From existing data
Creating record arrays (
numpy.rec
)
Creating character arrays (
numpy.char
)
Numerical ranges
Building matrices
The Matrix class
Array manipulation routines
Changing array shape
Transpose-like operations
Changing number of dimensions
Changing kind of array
Joining arrays
Splitting arrays
Tiling arrays
Adding and removing elements
Rearranging elements
Indexing routines
Generating index arrays
Indexing-like operations
Inserting data into arrays
Iterating over arrays
Data type routines
Creating data types
Data type information
Data type testing
Miscellaneous
Input and output
NPZ files
Text files
String formatting
Memory mapping files
Text formatting options
Base-n representations
Data sources
Fourier transforms (
numpy.fft
)
1-dimensional
2-dimensional
N-dimensional
Hermite symmetric
Real-valued
Helper routines
Linear algebra (
numpy.linalg
)
Matrix and vector products
Decompositions
Matrix eigenvalues
Norms and other numbers
Solving equations and inverting matrices
Exceptions
Random sampling (
numpy.random
)
Simple random data
Permutations
Distributions
Random generator
Sorting and searching
Sorting
Searching
Logic functions
Truth value testing
Array contents
Array type testing
Logical operations
Comparison
Binary operations
Elementwise bit operations
Bit packing
Output formatting
Statistics
Extremal values
Averages and variances
Correlating
Histograms
Mathematical functions
Trigonometric functions
Hyperbolic functions
Rounding
Sums, products, differences
Exponents and logarithms
Other special functions
Floating point routines
Arithmetic operations
Handling complex numbers
Miscellaneous
Functional programming
Polynomials
Basics
Fitting
Calculus
Arithmetic
Warnings
Financial functions
Simple financial functions
Set routines
Making proper sets
Boolean operations
Window functions
Various windows
Floating point error handling
Setting and getting error handling
Internal functions
Masked array operations
Constants
Creation
Inspecting the array
Manipulating a MaskedArray
Operations on masks
Conversion operations
Masked arrays arithmetics
Numpy-specific help functions
Finding help
Reading help
Miscellaneous routines
Buffer objects
Performance tuning
Mathematical functions with automatic domain (
numpy.emath
)
Matrix library (
numpy.matlib
)
Optionally Scipy-accelerated routines (
numpy.dual
)
Linear algebra
FFT
Other
Numarray compatibility (
numpy.numarray
)
Old Numeric compatibility (
numpy.oldnumeric
)
C-Types Foreign Function Interface (
numpy.ctypeslib
)
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