Create a numpy program that gets info about the sum function.

The sum function in Numpy adds up the total of the elements present inside an array.


import numpy as np


sum(a, axis=None, dtype=None, out=None, keepdims=,

Sum of array elements over a given axis.

a : array_like
    Elements to sum.
axis : None or int or tuple of ints, optional
    Axis or axes along which a sum is performed.  The default,
    axis=None, will sum all of the elements of the input array.  If
    axis is negative it counts from the last to the first axis.

    .. versionadded:: 1.7.0

    If axis is a tuple of ints, a sum is performed on all of the axes
    specified in the tuple instead of a single axis or all the axes as
dtype : dtype, optional
    The type of the returned array and of the accumulator in which the
    elements are summed.  The dtype of `a` is used by default unless `a`
    has an integer dtype of less precision than the default platform
    integer.  In that case, if `a` is signed then the platform integer
    is used while if `a` is unsigned then an unsigned integer of the
    same precision as the platform integer is used.
out : ndarray, optional
    Alternative output array in which to place the result. It must have
    the same shape as the expected output, but the type of the output
    values will be cast if necessary.
keepdims : bool, optional
    If this is set to True, the axes which are reduced are left
    in the result as dimensions with size one. With this option,
    the result will broadcast correctly against the input array.

    If the default value is passed, then `keepdims` will not be
    passed through to the `sum` method of sub-classes of
    `ndarray`, however any non-default value will be.  If the
    sub-class' method does not implement `keepdims` any
    exceptions will be raised.
initial : scalar, optional
    Starting value for the sum. See `~numpy.ufunc.reduce` for details.

    .. versionadded:: 1.15.0

sum_along_axis : ndarray
    An array with the same shape as `a`, with the specified
    axis removed.   If `a` is a 0-d array, or if `axis` is None, a scalar
    is returned.  If an output array is specified, a reference to
    `out` is returned.

See Also
ndarray.sum : Equivalent method.

cumsum : Cumulative sum of array elements.

trapz : Integration of array values using the composite trapezoidal rule.

mean, average

Arithmetic is modular when using integer types, and no error is
raised on overflow.

The sum of an empty array is the neutral element 0:

>>> np.sum([])

>>> np.sum([0.5, 1.5])
>>> np.sum([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
>>> np.sum([[0, 1], [0, 5]])
>>> np.sum([[0, 1], [0, 5]], axis=0)
array([0, 6])
>>> np.sum([[0, 1], [0, 5]], axis=1)
array([1, 5])

If the accumulator is too small, overflow occurs:

>>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)

You can also start the sum with a value other than zero:

>>> np.sum([10], initial=5)

Code Editor

import numpy as np print(