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numpy.ptp () in Python

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numpy.ptp() are used to play an important role in statistics by defining a range of given numbers. Range = maximum value — minimum value.

Syntax: ndarray.ptp (axis = None, out = None)
Parameters:
arr: input array.
axis: axis along which we want the range value. Otherwise, it will consider arr to be flattened (works on all the axis). axis = 0 means along the column and axis = 1 means working along the row.
out: [ndarray, optional] Different array in which we want to place the result. The array must have same dimensions as expected output.

Return: Range of the array (a scalar value if axis is none) or array with range of values ​​along specified axis.

Code # 1: Work

# Python program illustrating
# numpy.ptp () method

 

import numpy as np

 
# 1D array

arr = [ 1 , 2 , 7 , 20 , np.nan]

print ( "arr:" , arr) 

print ( "Range of arr:" , np.ptp (arr))

 

1D array 

arr = [ 1 , 2 , 7 , 10 , 16 ]

print ( "arr:" , ar r) 

print ( "Range of arr: " , np.ptp (arr))

Output:

 arr: [1, 2, 7, 20, nan] Range of arr: nan arr: [1, 2, 7, 10, 16] Range of arr: 15 

Code # 2:

# Python program illustrating
# numpy.ptp () method

  

import numpy as np

 
# 3D array

arr = [[ 14 , 17  , 12 , 33 , 44 ], 

[ 15 , 6 , 27 , 8 , 19 ], 

[ 23 , 2 , 54 , 1 , 4 ,]] 

print  ( "arr:" , arr) 

 
# Flattened array range

print ( "Range of arr, axis = None:" , np.ptp (arr)) 

 
# Range along the first axis
# 0 axis means vertical

print ( "Range of arr, axis = 0:" , np.ptp (arr, axis = 0 )) 

 
# Range along the second axis
# axis 1 means horizontal

print ( " Min of arr, axis = 1: " , np.ptp (arr, axis = 1 )) 

Output:

 arr: [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4]] Range of arr, axis = None: 53 Range of arr, axis = 0: [9 15 42 32 40] Min of arr, axis = 1: [32 21 53] 

Code # 3:

# Python program illustrating
# numpy.ptp () method

 

import numpy as np

 

arr1 = np.arange ( 5

print ( "Initial arr1:" , arr1)

  
# using the out parameter

np.ptp (arr, axis = 0 , out = arr1)

 

print ( " Changed arr1 (having results): " , arr1)

Output:

 Initial arr1: [0 1 2 3 4] Changed arr1 (having results): [9 15 42 32 40] 

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