NumPy: How to Calculate the Difference Between Neighboring Elements in Array
Last Updated :
09 Feb, 2024
To calculate the difference between neighboring elements in an array using the NumPy library we use numpy.diff() method of NumPy library.
It is used to find the n-th discrete difference along the given axis.
The first output is given by:
difference[i] = a[i+1] - a[i]
Example:
Python NumPy program to calculate differences between neighboring elements in a 2d NumPy array
Python3
import numpy as np
arr = np.array([[ 10 , 12 , 14 ],
[ 25 , 35 , 45 ],
[ 12 , 18 , 20 ]])
result = np.diff(arr, axis = 0 )
print (result)
|
Output:
[[ 15 23 31]
[-13 -17 -25]]
Syntax
Syntax: numpy.diff(a, n=1, axis=-1, prepend=<no value>, append=<no value>)
Parameters
- a: Input array
- n: The number of times values are differenced.
- axis: The axis along which the difference is taken, default is the last axis.
- prepend, append: Values to prepend or append to a along axis prior to performing the difference.
Returns: returns the n-th differences
Let’s check some examples of how to calculate the difference between neighboring elements in an array using NumPy to get a better understanding:
More Examples
Let’s look at examples for 1D and 2D arrays:
Calculating Differences Between Consecutive Elements in a 1D Numpy Array
Python3
import numpy as np
arr = np.array([ 1 , 12 , 3 , 14 , 5 ,
16 , 7 , 18 , 9 , 110 ])
result = np.diff(arr)
print (result)
|
Output:
[ 11 -9 11 -9 11 -9 11 -9 101]
Calculating Differences Between Neighboring Elements Along Rows in a 2D NumPy Array
Python3
import numpy as np
arr = np.array([[ 10 , 12 , 14 ],
[ 25 , 35 , 45 ],
[ 12 , 18 , 20 ]])
result = np.diff(arr, axis = 1 )
print (result)
|
Output:
[[ 2 2]
[10 10]
[ 6 2]]
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