 # numpy.percentile () in python

`numpy.percentile()` used to calculate the n-th precentile of data (array elements) along the specified axis.

Syntax: numpy.percentile (arr, n, axis = None, out = None)
Parameters:
arr: input array.
n: percentile value.
axis: axis along which we want to calculate the percentile 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: Different array in which we want to place the result. The array must have same dimensions as expected output.

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

Code # 1: Work

 ` # Python program illustrating ` ` # numpy.percentile () method `   ` import ` ` numpy as np `   ` # 1D array ` ` arr ` ` = ` ` [` ` 20 ` `, ` ` 2 , 7 , 1 , 34 ] ```` print ( "arr:" , arr)  print ( " 50th percentile of arr: " ,    np.percentile (arr, 50 )) print ( "25th percentile of arr:" , np.percentile (arr, 25 )) print ( "75th percentile of arr:" , np.percentile (arr, 75 )) ```

Output:

``` arr: [20, 2, 7, 1, 34] 30th percentile of arr: 7.0 25th percentile of arr: 2.0 75th percentile of arr: 20.0    Code # 2:            ` # Python program illustrating `  ` # numpy.percentile () method `      ` import ` ` numpy as np `    ` # 2D array `   ` arr ` ` = ` ` [[` ` 14 ` `, `  17  `, ` ` 12 ` `,   33  ,   44  ], ``    [  15  ,   6  ,   27  ,   8  ,   19  ],     [  23  ,   2  ,   54  ,   1   ,   4  ,]]    print   (  "arr:"  , arr)       # Flattened array percentile     print   (  "50th Percentile of arr, axis = None:"  ,      np.percentile (arr,   50  ))    print   (  "0th Percentile of arr, axis = None:"  ,     np.percentile (arr,   0  ))       # Axis percentile = 0     print   (  "50th Percentile of arr, axis = 0:"  ,      np.percentile (arr,   50  , axis   =   0  ))     print   (  "0th Percentile of arr, axis = 0: " ,      np.percentile (arr,   0  , axis   =   0  )) `     Output:    arr: [[14, 17, 12, 33, 44], [15, 6, 27, 8 , 19], [23, 2, 54, 1, 4]] 50th Percentile of arr, axis = None: 15.0 0th Percentile of arr, axis = None: 1.0 50th Percentile of arr, axis = 0: [15. 6. 27. 8. 19.] 0th Percentile of arr, axis = 0: [14. 2. 12. 1. 4.] 50th Percentile of arr, axis = 1: [17. 15. 4.] 0th Percentile of arr, axis = 1: [12. 6. 1.]
Code # 3:

` # Python program illustrating `  ` # numpy.percentile () method `

` import ` ` numpy as np `
` # 2D array `
` arr ` ` = ` ` [[` ` 14 ` `, ` ` 17 ` `, ` ` 12 ` `, ` ` 33 ` `, ` ` 44 ` `], `
` [` ` 15 ` ,  ` 6 ` `, ` ` 27 ` `, ` ` 8 ` `, ` ` 19 ` `], `
` [` ` 23 ` `, ` ` 2 ` `,   54  ,   1  ,   4  ,]] ````
print   (  "arr:"  , arr)
# Axis percentile = 1
print   ( " 50th Percentile of arr, axis = 1: " ,
np.percentile (arr,   50  , axis   =   1  ))
print   (  "0th Percentile of arr, axis = 1:"  ,
np.percentile (arr,   0  , axis   =   1  ))

print   (  "0th Percentile of arr, axis = 1:"  ,
np.percentile (arr,   50  , axis   =   1  , keepdims   =   True  ))
print   (  "0th Percentile of arr, axis = 1: " ,
np. percentile (arr,   0  , axis   =   1  , keepdims   =   True  ))
```

Output:
arr: [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1 , 4]] 0th Percentile of arr, axis = 1: [[17.] [15.] [4.]] 0th Percentile of arr, axis = 1: [[12.] [6.] [1.]]

```