class numpy.ndarray

An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an integer, a floating point number, or something else, etc.)

Arrays should be constructed using array, zeros or empty (refer to the See Also section below). The parameters given here refer to a low-level method (ndarray(...)) for instantiating an array.

For more information, refer to the numpy module and examine the the methods and attributes of an array.

Parameters :

(for the __new__ method; see Notes below) :

shape : tuple of ints

Shape of created array.

dtype : data-type, optional

Any object that can be interpreted as a numpy data type.

buffer : object exposing buffer interface, optional

Used to fill the array with data.

offset : int, optional

Offset of array data in buffer.

strides : tuple of ints, optional

Strides of data in memory.

order : {‘C’, ‘F’}, optional

Row-major or column-major order.

See also

Construct an array.
Create an array, each element of which is zero.
Create an array, but leave its allocated memory unchanged (i.e., it contains “garbage”).
Create a data-type.


There are two modes of creating an array using __new__:

  1. If buffer is None, then only shape, dtype, and order are used.
  2. If buffer is an object exposing the buffer interface, then all keywords are interpreted.

No __init__ method is needed because the array is fully initialized after the __new__ method.


These examples illustrate the low-level ndarray constructor. Refer to the See Also section above for easier ways of constructing an ndarray.

First mode, buffer is None:

>>> np.ndarray(shape=(2,2), dtype=float, order='F')
array([[ -1.13698227e+002,   4.25087011e-303],
       [  2.88528414e-306,   3.27025015e-309]])         #random

Second mode:

>>> np.ndarray((2,), buffer=np.array([1,2,3]),
...            offset=np.int_().itemsize,
...            dtype=int) # offset = 1*itemsize, i.e. skip first element
array([2, 3])


dtype Create a data type object.
imag(val) Return the imaginary part of the elements of the array.
real(val) Return the real part of the elements of the array.
size(a[, axis]) Return the number of elements along a given axis.
nbytes Base object for a dictionary for look-up with any alias for an array dtype.
ndim(a) Return the number of dimensions of an array.
shape(a) Return the shape of an array.
ctypes create and manipulate C data types in Python


all(a[, axis, out]) Test whether all array elements along a given axis evaluate to True.
any(a[, axis, out]) Test whether any array element along a given axis evaluates to True.
argmax(a[, axis]) Indices of the maximum values along an axis.
argmin(a[, axis]) Return the indices of the minimum values along an axis.
argsort(a[, axis, kind, order]) Returns the indices that would sort an array.
choose(a, choices[, out, mode]) Construct an array from an index array and a set of arrays to choose from.
clip(a, a_min, a_max[, out]) Clip (limit) the values in an array.
compress(condition, a[, axis, out]) Return selected slices of an array along given axis.
conj() Return the complex conjugate, element-wise.
conjugate() Return the complex conjugate, element-wise.
copy(a) Return an array copy of the given object.
cumprod(a[, axis, dtype, out]) Return the cumulative product of elements along a given axis.
cumsum(a[, axis, dtype, out]) Return the cumulative sum of the elements along a given axis.
diagonal(a[, offset, axis1, axis2]) Return specified diagonals.
dot(a, b) Dot product of two arrays.
max(a[, axis, out]) Return the maximum of an array or maximum along an axis.
mean(a[, axis, dtype, out]) Compute the arithmetic mean along the specified axis.
min(a[, axis, out]) Return the minimum of an array or minimum along an axis.
nonzero(a) Return the indices of the elements that are non-zero.
prod(a[, axis, dtype, out]) Return the product of array elements over a given axis.
ptp(a[, axis, out]) Range of values (maximum - minimum) along an axis.
put(a, ind, v[, mode]) Replaces specified elements of an array with given values.
ravel(a[, order]) Return a flattened array.
repeat(a, repeats[, axis]) Repeat elements of an array.
reshape(a, newshape[, order]) Gives a new shape to an array without changing its data.
resize(a, new_shape) Return a new array with the specified shape.
round(a[, decimals, out]) Round an array to the given number of decimals.
searchsorted(a, v[, side]) Find indices where elements should be inserted to maintain order.
sort(a[, axis, kind, order]) Return a sorted copy of an array.
squeeze(a) Remove single-dimensional entries from the shape of an array.
std(a[, axis, dtype, out, ddof]) Compute the standard deviation along the specified axis.
sum(a[, axis, dtype, out]) Sum of array elements over a given axis.
swapaxes(a, axis1, axis2) Interchange two axes of an array.
take(a, indices[, axis, out, mode]) Take elements from an array along an axis.
trace(a[, offset, axis1, axis2, dtype, out]) Return the sum along diagonals of the array.
transpose(a[, axes]) Permute the dimensions of an array.
var(a[, axis, dtype, out, ddof]) Compute the variance along the specified axis.

Previous topic


This Page