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What is the numpy.ediff1d() 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.ediff1d() function in NumPy is used to compute the differences between consecutive elements of an input array.

Syntax

numpy.ediff1d(ary, to_end=None, to_begin=None)

Parameters

The numpy.ediff1d() function takes the following parameters:

  • ary: This is the input array.

  • to_end: These are the numbers (if any) that are to be appended at the end of the array containing the resulting differences.

  • to_begin: These are the numbers (if any) that are to be prepended at the beginning of the array containing the resulting differences.

Return value

An array is returned which contains the following elements:

  • The appended and prepended values (if any) at the end and start of the array respectively.

  • The differences between the consecutive elements of the original array.

Note: If we want to append or prepend more than one element to the output array, we enclose those elements within a [], separated by commas. For example,numpy.ediff1d(ary, to_end=[4, 5], to_begin=[1, 2, 3]).

Example

import numpy as np
# creating an array
a = np.array([1, 2, 3, 4, 5])
# Implementing the numpy.ediff1d() function
# taking the differences and also appending and prepending 3 and 2 respectively
myarray = np.ediff1d(a, 2, 3)
print("Input array: ", a)
print("Output array: ", myarray)
Implementing the numpy.ediff1d() function

Explanation

  • Line 1: We import the numpy module.

  • Line 4: We create an array, a, using the np.array() method.

  • Line 8: We implement the numpy.ediff1d() function on the array and assign it to a variable, myarray.

  • Line 10: We print the input array, a.

  • Line 11: We print the output array, myarray.

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function
numpy
python
communitycreator

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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