NumPy

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, \*[, dtype])

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[, copy, sparse, indexing])

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.