SciPy

This is documentation for an old release of NumPy (version 1.17). Read this page in the documentation of the latest stable release (version 2.2).

Array creation routines

See also

Array creation

Ones and zeros

empty(shape[, dtype, order]) Return a new array of given shape and type, without initializing entries.
empty_like(prototype[, dtype, order, subok, …]) Return a new array with the same shape and type as a given array.
eye(N[, M, k, dtype, order]) Return a 2-D array with ones on the diagonal and zeros elsewhere.
identity(n[, dtype]) Return the identity array.
ones(shape[, dtype, order]) Return a new array of given shape and type, filled with ones.
ones_like(a[, dtype, order, subok, shape]) Return an array of ones with the same shape and type as a given array.
zeros(shape[, dtype, order]) Return a new array of given shape and type, filled with zeros.
zeros_like(a[, dtype, order, subok, shape]) Return an array of zeros with the same shape and type as a given array.
full(shape, fill_value[, dtype, order]) Return a new array of given shape and type, filled with fill_value.
full_like(a, fill_value[, dtype, order, …]) Return a full array with the same shape and type as a given array.

From existing data

array(object[, dtype, copy, order, subok, ndmin]) Create an array.
asarray(a[, dtype, order]) Convert the input to an array.
asanyarray(a[, dtype, order]) Convert the input to an ndarray, but pass ndarray subclasses through.
ascontiguousarray(a[, dtype]) Return a contiguous array (ndim >= 1) in memory (C order).
asmatrix(data[, dtype]) Interpret the input as a matrix.
copy(a[, order]) Return an array copy of the given object.
frombuffer(buffer[, dtype, count, offset]) Interpret a buffer as a 1-dimensional array.
fromfile(file[, dtype, count, sep, offset]) Construct an array from data in a text or binary file.
fromfunction(function, shape, \*\*kwargs) Construct an array by executing a function over each coordinate.
fromiter(iterable, dtype[, count]) Create a new 1-dimensional array from an iterable object.
fromstring(string[, dtype, count, sep]) A new 1-D array initialized from text data in a string.
loadtxt(fname[, dtype, comments, delimiter, …]) Load data from a text file.

Creating record arrays (numpy.rec)

Note

numpy.rec is the preferred alias for numpy.core.records.

core.records.array(obj[, dtype, shape, …]) Construct a record array from a wide-variety of objects.
core.records.fromarrays(arrayList[, dtype, …]) create a record array from a (flat) list of arrays
core.records.fromrecords(recList[, dtype, …]) create a recarray from a list of records in text form
core.records.fromstring(datastring[, dtype, …]) create a (read-only) record array from binary data contained in a string
core.records.fromfile(fd[, dtype, shape, …]) Create an array from binary file data

Creating character arrays (numpy.char)

Note

numpy.char is the preferred alias for numpy.core.defchararray.

core.defchararray.array(obj[, itemsize, …]) Create a chararray.
core.defchararray.asarray(obj[, itemsize, …]) Convert the input to a chararray, copying the data only if necessary.

Numerical ranges

arange([start,] stop[, step,][, dtype]) Return evenly spaced values within a given interval.
linspace(start, stop[, num, endpoint, …]) Return evenly spaced numbers over a specified interval.
logspace(start, stop[, num, endpoint, base, …]) Return numbers spaced evenly on a log scale.
geomspace(start, stop[, num, endpoint, …]) Return numbers spaced evenly on a log scale (a geometric progression).
meshgrid(\*xi, \*\*kwargs) Return coordinate matrices from coordinate vectors.
mgrid nd_grid instance which returns a dense multi-dimensional “meshgrid”.
ogrid nd_grid instance which returns an open multi-dimensional “meshgrid”.

Building matrices

diag(v[, k]) Extract a diagonal or construct a diagonal array.
diagflat(v[, k]) Create a two-dimensional array with the flattened input as a diagonal.
tri(N[, M, k, dtype]) An array with ones at and below the given diagonal and zeros elsewhere.
tril(m[, k]) Lower triangle of an array.
triu(m[, k]) Upper triangle of an array.
vander(x[, N, increasing]) Generate a Vandermonde matrix.

The Matrix class

mat(data[, dtype]) Interpret the input as a matrix.
bmat(obj[, ldict, gdict]) Build a matrix object from a string, nested sequence, or array.