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What is the numpy.nancumprod() function in NumPy?

Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

Overview

The numpy.nancumprod() function in NumPy is used to return the cumulative product of each element of an input array over a given axis in such a way that NaN values are treated as 1.

Syntax

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

Parameter

The numpy.nancumprod() function takes the following parameter values:

  • a (required): This is the input array containing numbers to be computed.
  • axis (optional): This is the axis along which the product is determined.
  • dtype (optional): This is the data type of the output array.
  • out (optional): This is the alternate array where the result is placed.

Return value

The numpy.nancumprod() function returns an output array holding the result.

Example

import numpy as np
# creating an array
x = np.array([1, 2, np.nan, 2, np.nan])
# Implementing the nancumprod() function
myarray = np.nancumprod(x, axis=0)
print(x)
print(myarray)
Implementing the nan.cumprod() function

Explanation

  • Line 1: We import the numpy module.
  • Line 4: We create an array, x, using the array() method.
  • Line 7: We implement the np.nancumprod() function on the array. The result is assigned to a variable, myarray.
  • Line 9: We print the input array x.
  • Line 10: We print the variable myarray.

Note: It is worth remembering that NaN values are treated as 1.

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nancumprod
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CONTRIBUTOR

Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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