# 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]) 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]) 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, subok]) 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]) 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.

Routines

numpy.empty