.nansum()

In NumPy, the .nansum() function calculates the sum of array elements, treating NaN (Not a Number) values as zero. It ignores any NaN values in the array during the summation process, ensuring accurate results even with missing data.

Syntax

numpy.nansum(a, axis=None, dtype=None, out=None, keepdims=False)

• a: This is the array whose elements are to be summed, with NaN values ignored.
• axis (Optional): The axis or axes along which the sum is computed. By default, the sum is computed over all the elements in the array.
• dtype (Optional): The type of the returned array. If not specified, it is inferred from the input array.
• out (Optional): A location to store the result. If provided, the result will be stored in this array. It must have the same shape as the output.
• keepdims (Optional): If set to True, the reduced axes are retained in the result as dimensions with size one. Otherwise, the axes are removed.

Example 1

The following example demonstrates the usage of the .nansum() function:

import numpy as np

# Array with NaN values
arr = np.array([1, 2, np.nan, 4, np.nan, 6])

# Compute the sum, ignoring NaN values
sum_result = np.nansum(arr)

print(sum_result)

The output of the above code is shown below:

13.0

Example 2

In the example below, the .nansum() function computes the sum of the array elements, ignoring any NaN values, both for the entire array and along specified axes:

import numpy as np

# 2D array with NaN values
arr = np.array([[1, 2, np.nan, 4],
                [5, np.nan, 7, 8],
                [9, 10, 11, np.nan]])

# Compute the sum along the entire array, ignoring NaN values
sum_result_all = np.nansum(arr)

# Compute the sum along each column (axis=0), ignoring NaN values
sum_result_columns = np.nansum(arr, axis=0)

# Compute the sum along each row (axis=1), ignoring NaN values
sum_result_rows = np.nansum(arr, axis=1)

print("Sum of all elements (ignoring NaN):", sum_result_all)
print("Sum of each column (ignoring NaN):", sum_result_columns)
print("Sum of each row (ignoring NaN):", sum_result_rows)

This outputs the following:

Sum of all elements (ignoring NaN): 57.0
Sum of each column (ignoring NaN): [15. 12. 18. 12.]
Sum of each row (ignoring NaN): [ 7. 20. 30.]

Codebyte Example

Run the following codebyte example to understand how the .nansum() function works:

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