# sciPy stats.scoreatpercentile() function | Python

`scipy.stats.scoreatpercentile(a, score, kind='rank') ` function helps us to calculate the score at a given percentile of the input array.

The score at percentile = 50 is the median. If the desired quantile lies between two data points, we interpolate between them, according to the value of interpolation.

Parameters :
arr : [array_like] input array.
per : [array_like] Percentile at which we need the score.
limit : [tuple] the lower and upper limits within which to compute the percentile.
axis : [int] axis along which we need to calculate the score.

Results : Score at Percentile relative to the array element.

Code #1:

 `# scoreatpercentile ` `from` `scipy ``import` `stats ` `import` `numpy as np  ` ` `  `# 1D array   ` `arr ``=` `[``20``, ``2``, ``7``, ``1``, ``7``, ``7``, ``34``, ``3``] ` ` `  `print``(``"arr : "``, arr)   ` ` `  `print` `(``"\nScore at 50th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``50``)) ` ` `  `print` `(``"\nScore at 90th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``90``)) ` ` `  `print` `(``"\nScore at 10th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``10``)) ` ` `  `print` `(``"\nScore at 100th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``100``)) ` ` `  `print` `(``"\nScore at 30th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``30``)) `

Output:

```arr :  [20, 2, 7, 1, 7, 7, 34, 3]

Score at 50th percentile :  7.0

Score at 90th percentile :  24.2

Score at 10th percentile :  1.7

Score at 100th percentile :  34.0

Score at 30th percentile :  3.4
```

Code #2:

 `# scoreatpercentile ` `from` `scipy ``import` `stats ` `import` `numpy as np  ` ` `  `arr ``=` `[[``14``, ``17``, ``12``, ``33``, ``44``],    ` `       ``[``15``, ``6``, ``27``, ``8``, ``19``],   ` `       ``[``23``, ``2``, ``54``, ``1``, ``4``, ]]  ` ` `  `print``(``"arr : "``, arr)   ` ` `  `print` `(``"\nScore at 50th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``50``)) ` ` `  `print` `(``"\nScore at 50th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``50``, axis ``=` `1``)) ` ` `  `print` `(``"\nScore at 50th percentile : "``,  ` `       ``stats.scoreatpercentile(arr, ``50``, axis ``=` `0``)) `

Output:

```arr :  [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19], [23, 2, 54, 1, 4]]

Score at 50th percentile :  15.0

Score at 50th percentile :  [ 17.  15.   4.]

Score at 50th percentile :  [ 15.   6.  27.   8.  19.]
```

My Personal Notes arrow_drop_up Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.

Article Tags :

Be the First to upvote.

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.