Published Jun 4, 2022Updated May 15, 2024
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The .sum() function sums the elements of an array over a given axis.


numpy.sum(a, axis, dtype, out, keepdims, initial, where)

The a argument is required and represents the array of elements to sum. All other arguments are optional. Used by itself, a will result in a scalar that sums all the elements of the array.

.sum() provides the following arguments:

  • a: The array of elements to sum.
  • axis: An int or tuple of ints specifying the axis/axes along which to sum.
  • dtype: The type of the returned array and the accumulator used to sum elements. Defaults to the dtype of array.
  • out: An ndarray to receive result. Must have the same shape as expected output.
  • keepdims: A boolean if true will keep reduced axes in the result as dimensions with size one.
  • initial: The starting value for sum.
  • where: A boolean array that maps to array and selects elements to include into the sum.


The following example creates an array then uses a few .sum() operations to sum the elements.

import numpy as np
nd = np.array([[1,2,3],[4,5,6]])
print(np.sum(nd, axis=0))
print(np.sum(nd, axis=1))

This produces the following output:

[5 7 9]
[ 6 15]

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