# 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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