pydoc > numpy

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```html

📖 NAME

numpy

🚀 Quick Reference

Use Case	Command	Description
Create array from list	np.array([1,2,3])	📦 Create a NumPy array from a Python list
Array of zeros	np.zeros((3,4))	➿ Create an array filled with zeros
Array of ones	np.ones((2,2))	1️⃣ Create an array filled with ones
Evenly spaced values	np.arange(0,10,2)	🔢 Generate evenly spaced values within a range
Linear spacing	np.linspace(0,1,5)	📏 Generate linearly spaced numbers
Random numbers	np.random.rand(3,3)	🎲 Generate random numbers (uniform)
Matrix multiplication	np.dot(a,b) or a@b	✖️ Matrix multiplication (dot product)
Element‑wise operations	np.add(a,b) or a+b	➕ Add arrays element‑wise
Reshape array	np.reshape(a,(2,3))	🔀 Change the shape of an array
Statistical summary	np.mean(a, axis=0)	📊 Compute mean along an axis
Linear algebra	np.linalg.inv(a)	⚡ Compute matrix inverse
Fast Fourier Transform	np.fft.fft(a)	🌀 Compute 1‑D FFT

📝 DESCRIPTION

NumPy – Provides an array object of arbitrary homogeneous items, fast mathematical operations over arrays, Linear Algebra, Fourier Transforms, Random Number Generation.

📖 How to use the documentation

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 TAB-completion and introspection capabilities.

The docstring examples assume that numpy has been imported as np:

>>> import numpy as np

Code snippets are indicated by three greater‑than signs:

>>> x = 42
>>> x = x + 1

Use the built‑in 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.

To search for documents containing a keyword, do:

>>> np.lookfor('keyword')
... # doctest: +SKIP

General‑purpose documents like a glossary and help on the basic concepts of numpy are available under the doc sub‑module:

>>> from numpy import doc
>>> help(doc)
... # doctest: +SKIP

📂 Available subpackages

• doc – Topical documentation on broadcasting, indexing, etc.
• lib – Basic functions used by several sub‑packages.
• random – Core Random Tools
• linalg – Core Linear Algebra Tools
• fft – Core FFT routines
• polynomial – Polynomial tools
• testing – NumPy testing tools
• f2py – Fortran to Python Interface Generator.
• distutils – Enhancements to distutils with support for Fortran compilers support and more.

🛠️ Utilities

• test – Run numpy unittests
• show_config – Show numpy build configuration
• dual – Overwrite certain functions with high‑performance SciPy tools. Deprecated.
• matlib – Make everything matrices.
• __version__ – NumPy version string

💻 Viewing documentation using IPython

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>, or use np.*cos*?<ENTER> 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).

🔄 Copies vs. in‑place operation

Most of the functions in numpy return a copy of the array argument (e.g., np.sort). In‑place 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.

📦 PACKAGE CONTENTS

__config__
_distributor_init
_globals
_pytesttester
_version
compat (package)
conftest
core (package)
ctypeslib
distutils (package)
doc (package)
dual
f2py (package)
fft (package)
lib (package)
linalg (package)
ma (package)
matlib
matrixlib (package)
polynomial (package)
random (package)
setup
testing (package)
tests (package)
typing (package)
version

📂 SUBMODULES

_mat
char
emath
rec

🏷️ CLASSES

🔷 builtins.DeprecationWarning(builtins.Warning) – ModuleDeprecationWarning

🔷 builtins.IndexError(builtins.LookupError) – AxisError(builtins.ValueError, builtins.IndexError)

🔷 builtins.RuntimeError(builtins.Exception) – TooHardError

🔷 builtins.RuntimeWarning(builtins.Warning) – ComplexWarning

🔷 builtins.UserWarning(builtins.Warning) – RankWarning, VisibleDeprecationWarning

🔷 builtins.ValueError(builtins.Exception) – AxisError(builtins.ValueError, builtins.IndexError)

🔷 builtins.bytes(builtins.object) – bytes_(builtins.bytes, character)

🔷 builtins.object – DataSource, MachAr, broadcast, busdaycalendar, dtype, finfo, flatiter, format_parser, generic, iinfo, ndarray, ndenumerate, ndindex, nditer, poly1d, ufunc, vectorize

🔷 builtins.str(builtins.object) – str_(builtins.str, character)

🔷 contextlib.ContextDecorator(builtins.object) – errstate

📌 class AxisError(builtins.ValueError, builtins.IndexError)

Axis supplied was invalid.

• __init__(self, axis, ndim=None, msg_prefix=None) – Initialize self.
• __weakref__ – list of weak references to the object (if defined)

📌 class ComplexWarning(builtins.RuntimeWarning)

The warning raised when casting a complex dtype to a real dtype.

• __weakref__ – list of weak references to the object (if defined)

📌 class DataSource(builtins.object)

DataSource(destpath='.')

A generic data source file (file, http, ftp, …).

• __init__(self, destpath='.') – Create a DataSource with a local path.
• abspath(self, path) – Return absolute path of file in the DataSource directory.
• exists(self, path) – Test if path exists.
• open(self, path, mode='r', encoding=None, newline=None) – Open and return file‑like object.

📌 class MachAr(builtins.object)

Diagnosing machine parameters.

• __init__(self, float_conv=float, int_conv=int, float_to_float=float, float_to_str=..., title='Python floating point number') – Initialize self.
• __str__(self) – Return str(self).

📌 class ModuleDeprecationWarning(builtins.DeprecationWarning)

Module deprecation warning.

📌 class RankWarning(builtins.UserWarning)

Issued by polyfit when the Vandermonde matrix is rank deficient.

📌 class TooHardError(builtins.RuntimeError)

Raised when a computation is too hard (e.g., in shares_memory).

📌 class VisibleDeprecationWarning(builtins.UserWarning)

Visible deprecation warning.

📌 class bool_(generic)

Boolean type (True or False), stored as a byte.

• __and__(self, value, /) – Return self&value.
• __bool__(self, /) – True if self else False
• __eq__(self, value, /) – Return self==value.
• __ge__(self, value, /) – Return self>=value.
• __gt__(self, value, /) – Return self>value.
• __hash__(self, /) – Return hash(self).
• … (and many more inherited from generic)

📌 class broadcast(builtins.object)

Produce an object that mimics broadcasting.

• __iter__(self, /) – Implement iter(self).
• __next__(self, /) – Implement next(self).
• reset(...) – Reset the broadcasted result's iterator(s).
• index – current index in broadcasted result
• iters – tuple of iterators along components
• nd – Number of dimensions of broadcasted result
• ndim – Alias for nd
• numiter – Number of iterators
• shape – Shape of broadcasted result
• size – Total size

📌 class busdaycalendar(builtins.object)

A business day calendar object.

• __init__(self, /, *args, **kwargs) – Initialize self.
• holidays – A copy of the holiday array.
• weekmask – A copy of the seven‑element boolean mask indicating valid days.

📌 class dtype(builtins.object)

Create a data type object.

• __bool__(self, /) – True if self else False
• __eq__(self, value, /) – Return self==value.
• newbyteorder(...) – Return a new dtype with a different byte order.
• Properties: alignment, base, byteorder, char, descr, fields, flags, hasobject, isalignedstruct, isbuiltin, isnative, itemsize, kind, metadata, name, names, ndim, num, shape, str, subdtype, type

📌 class errstate(contextlib.ContextDecorator)

Context manager for floating‑point error handling.

• __init__(self, *, call=..., **kwargs) – Initialize self.
• __enter__(self)
• __exit__(self, *exc_info)

📌 class finfo(builtins.object)

Machine limits for floating point types.

• __repr__(self)
• __str__(self)
• Properties: bits, eps, epsneg, iexp, machar, machep, max, maxexp, min, minexp, negep, nexp, nmant, precision, resolution, tiny

📌 class flatiter(builtins.object)

Flat iterator object to iterate over arrays.

• __array__(...) – Get array from iterator
• copy(...) – Get a copy of the iterator as a 1‑D array.
• base – A reference to the array that is iterated over.
• coords – An N‑dimensional tuple of current coordinates.
• index – Current flat index into the array.

📌 class format_parser(builtins.object)

Class to convert formats, names, titles description to a dtype.

📌 class generic(builtins.object)

Base class for numpy scalar types.

• Many methods like __abs__, __add__, __array__, all, any, argmax, argmin, argsort, astype, byteswap, choose, clip, compress, conj, conjugate, copy, cumprod, cumsum, diagonal, dump, dumps, fill, flatten, getfield, item, itemset, max, mean, min, newbyteorder, nonzero, prod, ptp, put, ravel, repeat, reshape, resize, round, searchsorted, setfield, setflags, sort, squeeze, std, sum, swapaxes, take, tobytes, tofile, tolist, tostring, trace, transpose, var, view
• Data descriptors: T, __array_interface__, __array_priority__, __array_struct__, base, data, dtype, flags, flat, imag, itemsize, nbytes, ndim, real, shape, size, strides

📌 class iinfo(builtins.object)

Machine limits for integer types.

• __init__(self, int_type)
• __repr__(self)
• __str__(self)
• Properties: max, min

📌 class ndarray(builtins.object)

An array object represents a multidimensional, homogeneous array of fixed‑size items.

• Many methods: __abs__, __add__, __array__, all, any, argmax, argmin, argpartition, argsort, astype, byteswap, choose, clip, compress, conj, copy, cumprod, cumsum, diagonal, dot, dump, dumps, fill, flatten, getfield, item, itemset, max, mean, min, newbyteorder, nonzero, partition, prod, ptp, put, ravel, repeat, reshape, resize, round, searchsorted, setfield, setflags, sort, squeeze, std, sum, swapaxes, take, tobytes, tofile, tolist, tostring, trace, transpose, var, view
• Data descriptors: T, __array_finalize__, __array_interface__, __array_priority__, __array_struct__, base, ctypes, data, dtype, flags, flat, imag, itemsize, nbytes, ndim, real, shape, size, strides

📌 class ndenumerate(builtins.object)

Multidimensional index iterator.

• __init__(self, arr)
• __iter__(self)
• __next__(self) – Returns the index tuple and array value.

📌 class ndindex(builtins.object)

An N‑dimensional iterator object to index arrays.

• __init__(self, *shape)
• __iter__(self)
• __next__(self) – Returns a tuple of indices.
• ndincr(self) – Increment the multi‑dimensional index by one (deprecated).

📌 class nditer(builtins.object)

Efficient multi‑dimensional iterator object to iterate over arrays.

• __init__(self, /, *args, **kwargs)
• close(...) – Resolve all writeback semantics.
• copy(...) – Get a copy of the iterator in its current state.
• debug_print(...) – Print the current state.
• enable_external_loop(...) – Modify the iterator to behave as if the flag was specified.
• iternext(...) – Perform a single internal iteration.
• remove_axis(...) – Removes axis i.
• remove_multi_index(...) – Remove the multi_index flag.
• reset(...) – Reset the iterator to its initial state.
• Properties: dtypes, finished, has_delayed_bufalloc, has_index, has_multi_index, index, iterationneedsapi, iterindex, iterrange, itersize, itviews, multi_index, ndim, nop, operands, shape, value

📌 class poly1d(builtins.object)

A one‑dimensional polynomial class.

• __init__(self, c_or_r, r=False, variable=None)
• deriv(self, m=1) – Return a derivative.
• integ(self, m=1, k=0) – Return an antiderivative.
• Properties: o, order, r, roots, variable, c, coef, coefficients, coeffs

📌 class ufunc(builtins.object)

Functions that operate element by element on whole arrays.

• __call__(self, /, *args, **kwargs)
• accumulate(...) – Accumulate the result of applying the operator.
• at(...) – Performs unbuffered in place operation.
• outer(...) – Apply the ufunc to all pairs.
• reduce(...) – Reduces array's dimension by one.
• reduceat(...) – Performs a (local) reduce with specified slices.
• Properties: identity, nargs, nin, nout, ntypes, signature, types

📌 class vectorize(builtins.object)

Generalized function class.

• __init__(self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None)
• __call__(self, *args, **kwargs) – Return arrays with the results of pyfunc broadcast.

📌 Subclasses of ndarray

• chararray – Provides a convenient view on arrays of string and unicode values.
• matrix – A specialized 2‑D array that retains its 2‑D nature through operations.
• memmap – Create a memory‑map to an array stored in a binary file on disk.
• recarray – Construct an ndarray that allows field access using attributes.

📌 Scalar type classes (e.g., float64, int32, complex128, etc.)

Each numeric type has its own class with methods for arithmetic and type conversion. Full list: bool_, int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32, float64, float128, complex64, complex128, complex256, datetime64, timedelta64, bytes_, str_, void, object_, record, etc.

🔧 FUNCTIONS (selected)

• array(object, dtype=None, *, copy=True, order='K', subok=False, ndmin=0, like=None) – Create an array.
• zeros(shape, dtype=float, order='C', *, like=None) – Return a new array of given shape and type, filled with zeros.
• ones(shape, dtype=None, order='C', *, like=None) – Return a new array of given shape and type, filled with ones.
• full(shape, fill_value, dtype=None, order='C', *, like=None) – Return a new array of given shape and type, filled with fill_value.
• empty(shape, dtype=float, order='C', *, like=None) – Return a new array of given shape and type, without initializing entries.
• arange([start,] stop[, step,], dtype=None, *, like=None) – Return evenly spaced values within a given interval.
• linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0) – Return evenly spaced numbers over a specified interval.
• logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0) – Return numbers spaced evenly on a log scale.
• reshape(a, newshape, order='C') – Gives a new shape to an array without changing its data.
• ravel(a, order='C') – Return a contiguous flattened array.
• concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind") – Join a sequence of arrays along an existing axis.
• stack(arrays, axis=0, out=None) – Join a sequence of arrays along a new axis.
• split(ary, indices_or_sections, axis=0) – Split an array into multiple sub‑arrays as views.
• dot(a, b, out=None) – Dot product of two arrays.
• matmul(x1, x2, /, out=None, ...) – Matrix product of two arrays.
• sum(a, axis=None, dtype=None, out=None, keepdims=False, initial=0, where=True) – Sum of array elements over a given axis.
• mean(a, axis=None, dtype=None, out=None, keepdims=False, *, where=True) – Compute the arithmetic mean along the specified axis.
• std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, where=True) – Compute the standard deviation along the specified axis.
• var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, where=True) – Compute the variance along the specified axis.
• min(a, axis=None, out=None, keepdims=False, initial=..., where=...) – Return the minimum of an array or minimum along an axis.
• max(a, axis=None, out=None, keepdims=False, initial=..., where=...) – Return the maximum of an array or maximum along an axis.
• argmax(a, axis=None, out=None) – Returns the indices of the maximum values along an axis.
• argmin(a, axis=None, out=None) – Returns the indices of the minimum values along an axis.
• where(condition, [x, y]) – Return elements chosen from x or y depending on condition.
• nonzero(a) – Return the indices of the elements that are non‑zero.
• sort(a, axis=-1, kind=None, order=None) – Return a sorted copy of an array.
• argsort(a, axis=-1, kind=None, order=None) – Returns the indices that would sort an array.
• unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None) – Find the unique elements of an array.
• transpose(a, axes=None) – Reverse or permute the axes of an array.
• swapaxes(a, axis1, axis2) – Interchange two axes of an array.
• moveaxis(a, source, destination) – Move axes of an array to new positions.
• flip(m, axis=None) – Reverse the order of elements in an array along the given axis.
• fliplr(m) – Reverse the order of elements along axis 1 (left/right).
• flipud(m) – Reverse the order of elements along axis 0 (up/down).
• rot90(m, k=1, axes=(0,1)) – Rotate an array by 90 degrees in the plane specified by axes.
• pad(array, pad_width, mode='constant', **kwargs) – Pad an array.
• meshgrid(*xi, copy=True, sparse=False, indexing='xy') – Return coordinate matrices from coordinate vectors.
• mgrid, ogrid – nd_grid instances for creating dense/open multidimensional grids.
• ix_(*args) – Construct an open mesh from multiple sequences.
• einsum(subscripts, *operands, out=None, optimize=False) – Evaluates the Einstein summation convention.
• einsum_path(*operands, optimize='greedy') – Evaluates the lowest cost contraction order.
• histogram(a, bins=10, range=None, normed=None, weights=None, density=None) – Compute the histogram of a dataset.
• histogram2d(x, y, bins=10, range=None, normed=None, weights=None, density=None) – Compute the bi‑dimensional histogram.
• histogramdd(sample, bins=10, range=None, normed=None, weights=None, density=None) – Compute the multidimensional histogram.
• digitize(x, bins, right=False) – Return the indices of the bins to which each value in input array belongs.
• interp(x, xp, fp, left=None, right=None, period=None) – One‑dimensional linear interpolation.
• gradient(f, *varargs, axis=None, edge_order=1) – Return the gradient of an N‑dimensional array.
• trapz(y, x=None, dx=1.0, axis=-1) – Integrate along the given axis using the composite trapezoidal rule.
• diff(a, n=1, axis=-1, prepend=..., append=...) – Calculate the n‑th discrete difference.
• cumsum(a, axis=None, dtype=None, out=None) – Return the cumulative sum of the elements along a given axis.
• cumprod(a, axis=None, dtype=None, out=None) – Return the cumulative product of elements along a given axis.
• nansum, nanprod, nancumsum, nancumprod, nanmean, nanvar, nanstd, nanmin, nanmax, nanargmin, nanargmax, nanmedian, nanpercentile, nanquantile – NaN‑ignoring versions of corresponding functions.
• loadtxt(fname, dtype=float, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0, encoding='bytes', max_rows=None, *, like=None) – Load data from a text file.
• genfromtxt(fname, dtype=float, comments='#', delimiter=None, ...) – Load data from a text file with missing values handled.
• save(file, arr, allow_pickle=True, fix_imports=True) – Save an array to a binary file in .npy format.
• load(file, mmap_mode=None, allow_pickle=False, fix_imports=True, encoding='ASCII') – Load arrays or pickled objects from .npy, .npz or pickled files.
• savez, savez_compressed – Save several arrays into a single file in .npz format.
• polyfit, polyval, poly, roots, polyint, polyder, polyadd, polysub, polymul, polydiv – Old polynomial API.
• linalg.inv, linalg.det, linalg.eig, linalg.svd, etc. – Linear algebra operations (provided by numpy.linalg).
• fft.fft, fft.ifft, fft.fft2, etc. – Fast Fourier Transform routines (provided by numpy.fft).
• random.rand, random.randn, random.randint, random.seed, etc. – Random number generation (provided by numpy.random).

📊 DATA

• ALLOW_THREADS = 1
• BUFSIZE = 8192
• CLIP = 0
• ERR_CALL = 3
• ERR_DEFAULT = 521
• ERR_IGNORE = 0
• ERR_LOG = 5
• ERR_PRINT = 4
• ERR_RAISE = 2
• ERR_WARN = 1
• FLOATING_POINT_SUPPORT = 1
• FPE_DIVIDEBYZERO = 1
• FPE_INVALID = 8
• FPE_OVERFLOW = 2
• FPE_UNDERFLOW = 4
• False_ = False
• Inf = inf
• Infinity = inf
• MAXDIMS = 32
• MAY_SHARE_BOUNDS = 0
• MAY_SHARE_EXACT = -1
• NAN = nan
• NINF = -inf
• NZERO = -0.0
• NaN = nan
• PINF = inf
• PZERO = 0.0
• RAISE = 2
• SHIFT_DIVIDEBYZERO = 0
• SHIFT_INVALID = 9
• SHIFT_OVERFLOW = 3
• SHIFT_UNDERFLOW = 6
• ScalarType = (<class 'int'>, <class 'float'>, <class 'complex'>, ...)
• True_ = True
• UFUNC_BUFSIZE_DEFAULT = 8192
• UFUNC_PYVALS_NAME = 'UFUNC_PYVALS'
• WRAP = 1
• _UFUNC_API = <capsule object NULL>
• __NUMPY_SETUP__ = False
• __all__, __deprecated_attrs__, __expired_functions__, __git_version__
• Ufuncs: absolute, add, arccos, arccosh, arcsin, arcsinh, arctan, arctan2, arctanh, bitwise_and, bitwise_not, bitwise_or, bitwise_xor, cbrt, ceil, conj, conjugate, copysign, cos, cosh, deg2rad, degrees, divide, divmod, equal, exp, exp2, expm1, fabs, float_power, floor, floor_divide, fmax, fmin, fmod, frexp, gcd, greater, greater_equal, heaviside, hypot, invert, isfinite, isinf, isnan, isnat, lcm, ldexp, left_shift, less, less_equal, log, log10, log1p, log2, logaddexp, logaddexp2, logical_and, logical_not, logical_or, logical_xor, matmul, maximum, minimum, mod, modf, multiply, negative, nextafter, not_equal, positive, power, rad2deg, radians, reciprocal, remainder, right_shift, rint, sign, signbit, sin, sinh, spacing, sqrt, square, subtract, tan, tanh, trunc, true_divide
• Constants: e, euler_gamma, inf, nan, pi, newaxis, c_, r_, s_, index_exp, mgrid, ogrid, cast, nbytes, sctypeDict, sctypes, typecodes, tracemalloc_domain, little_endian

📌 VERSION

1.21.5

📁 FILE

/usr/lib/python3/dist-packages/numpy/__init__.py

```

📖 NAME 🚀 Quick Reference 📝 DESCRIPTION 📦 PACKAGE CONTENTS 📂 SUBMODULES 🏷️ CLASSES 🔧 FUNCTIONS (selected) 📊 DATA 📌 VERSION 📁 FILE