What is numpy.sum() in Python?
Python’s numpy.sum() computes the sum of an array over a specified axis.
Syntax
numpy.sum() is declared as follows:
numpy.sum(a, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
In the syntax above, a is the non-optional parameter, and the rest are optional parameters.
Parameters
numpy.sum() takes the following non-optional parameter:
a[array-like] - input array that contains the elements to be added.
numpy.sum() takes the following optional parameters:
-
axis[None, int, tuples of int] - axis along which we want the sum to be computed. If the axis is None, it will sum all the elements of the input array. If the axis is negative, the sum is computed from the last to the first axis. An axis with a value of 0 will compute the sum along the column, and an axis with a value of 1 will compute the sum along the row. -
out[ndarray] - represents the location into which the output is stored. -
dytpe[dtype] - represents the returned array type and the accumulator in which the elements are summed. By default, the dtype of the input array is used. -
keepdims[boolean] - true value ensures that the reduced axes are left as dimensions with size one in the output. This ensures that the output is broadcasted correctly against the input array. If a non-default value is passed, keepdims will be passed through to thesum()method of sub-classes ofndarray. In the case of the default value, this will not be done. -
initial[scalar] - minimum value of the output element. -
where[array_like of bool] - represents the elements to compare for the minimum.
Return value
numpy.sum() returns an array with the same shape as the input array, with the specified axis removed.
-
If
ais a zero-dimensional array, a scalar is returned. -
If
axisis None, a scalar is returned. -
If an output array is specified in the
outparameter, a reference tooutis returned.
Examples
The following example outputs the sum of the array arr where the axis parameter is not specified:
import numpy as nparr = np.array([1,2,5,6,0])print(np.sum(arr))
The example below outputs the sum of the array arr1 where axis is specified as 0 and 1.
import numpy as nparr1 = np.array([[2,4,5], [7,10,1]])#Sum along the columnsprint(np.sum(arr1, axis = 0))#Sum along the rowsprint(np.sum(arr1, axis = 1))
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