.cumsum()

In NumPy, the .cumsum() function computes the cumulative sum of elements in an array along a specified axis.

Syntax

numpy.cumsum(a, axis=None, dtype=None, out=None)

Parameters:

• a: The array of elements to calculate the cumulative sum of.
• axis (Optional): Axis along which the cumulative sum is computed. Default is None, meaning the sum is computed over the flattened array.
• dtype (Optional): The datatype of the returned array. If None, it defaults to the input array’s dtype.
• out (Optional): Alternative output array in which to place the result.

Return value:

Returns a new NumPy array containing the cumulative sum of elements along the specified axis.

Example

This example demonstrates how to compute the cumulative sum of a NumPy array using .cumsum():

import numpy as np

# Create an array
array = np.array([1, 2, 3, 4, 5])

# Compute the cumulative sum of the array
cumulative_sum = np.cumsum(array)

# Print out the original array
print("Original Array:", array)

# Print out the returned array
print("Cumulative Sum:", cumulative_sum)

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This produces the following output:

Original Array: [1 2 3 4 5]
Cumulative Sum: [ 1  3  6 10 15]

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Codebyte Example

Run the following codebyte example to better understand the .cumsum() function:

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