numpy.ptp()function plays an important role in statistics by finding out Range of given numbers. Range = max value - min value.
Syntax : ndarray.ptp(arr, 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: Working
Python
# 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 : ", arr)
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
# 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("\narr : \n", arr)
# Range of the flattened array
print("\nRange of arr, axis = None : ", np.ptp(arr))
# Range along the first axis
# axis 0 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
# Python Program illustrating
# numpy.ptp() method
import numpy as np
arr1 = np.arange(5)
print("\nInitial arr1 : ", arr1)
# using 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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