# numpy.ptp() in Python

• Last Updated : 23 Nov, 2021

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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