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numpy.diff() in Python
  • Last Updated : 27 Sep, 2019

numpy.diff(arr[, n[, axis]]) function is used when we calculate the n-th order discrete difference along the given axis. The first order difference is given by out[i] = arr[i+1] – arr[i] along the given axis. If we have to calculate higher differences, we are using diff recursively.

Synatx: numpy.diff()

Parameters:
arr : [array_like] Input array.
n : [int, optional] The number of times values are differenced.
axis : [int, optional] The axis along which the difference is taken, default is the last axis.

Returns : [ndarray]The n-th discrete difference. The output is the same as a except along axis where the dimension is smaller by n.

Code #1 :






# Python program explaining
# numpy.diff() method
  
    
# importing numpy
import numpy as geek 
  
# input array
arr = geek.array([1, 3, 4, 7, 9])
   
print("Input array  : ", arr)
print("First order difference  : ", geek.diff(arr))
print("Second order difference : ", geek.diff(arr, n = 2))
print("Third order difference  : ", geek.diff(arr, n = 3))
Output:
Input array  :  [1 3 4 7 9]
First order difference  :  [2 1 3 2]
Second order difference :  [-1  2 -1]
Third order difference  :  [ 3 -3]

 
Code #2 :




# Python program explaining
# numpy.diff() method
  
    
# importing numpy
import numpy as geek 
  
# input array
arr = geek.array([[1, 2, 3, 5], [4, 6, 7, 9]])
   
print("Input array  : ", arr)
print("Difference when axis is 0 : ", geek.diff(arr, axis = 0))
print("Difference when axis is 1 : ", geek.diff(arr, axis = 1))
Output:
Input array  :  [[1 2 3 5]
 [4 6 7 9]]
Difference with axis 0 :  [[3 4 4 4]]
Difference with axis 1 :  [[1 1 2]
 [2 1 2]]

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