numpy.nanpercentile() in Python

• Last Updated : 27 Oct, 2021

numpy.nanpercentile()function used to compute the nth percentile of the given data (array elements) along the specified axis ang ignores nan values.

Syntax : numpy.nanpercentile(arr, q, axis=None, out=None)
Parameters :
arr :input array.
q : 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 :Percentile of the array (a scalar value if axis is none) or array with percentiles of values along specified axis.

Code #1 : Working

 # Python Program illustrating # numpy.nanpercentile() method     import numpy as np    # 1D array arr = [20, 2, 7, np.nan, 34]print("arr : ", arr) print("30th 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))  print("\n30th percentile of arr : ",      np.nanpercentile(arr, 50))print("25th percentile of arr : ",       np.nanpercentile(arr, 25))print("75th percentile of arr : ",       np.nanpercentile(arr, 75))

Output :

arr :  [20, 2, 7, nan, 34]
30th percentile of arr :  nan
25th percentile of arr :  nan
75th percentile of arr :  nan

30th percentile of arr :  13.5
25th percentile of arr :  5.75
75th percentile of arr :  23.5

Code #2 :

 # Python Program illustrating # numpy.nanpercentile() method   import numpy as np  # 2D array arr = [[14, np.nan, 12, 33, 44],         [15, np.nan, 27, 8, 19],        [23, 2, np.nan, 1, 4,]] print("\narr : \n", arr)      # Percentile of the flattened array print("\n50th Percentile of arr, axis = None : ",       np.percentile(arr, 50)) print("\n50th Percentile of arr, axis = None : ",       np.nanpercentile(arr, 50)) print("0th Percentile of arr, axis = None : ",       np.nanpercentile(arr, 0))      # Percentile along the axis = 0 print("\n50th Percentile of arr, axis = 0 : ",       np.nanpercentile(arr, 50, axis =0)) print("0th Percentile of arr, axis = 0 : ",       np.nanpercentile(arr, 0, axis =0))   # Percentile along the axis = 1 print("\n50th Percentile of arr, axis = 1 : ",       np.nanpercentile(arr, 50, axis =1)) print("0th Percentile of arr, axis = 1 : ",       np.nanpercentile(arr, 0, axis =1))    print("\n0th Percentile of arr, axis = 1 : \n",       np.nanpercentile(arr, 50, axis =1, keepdims=True))print("\n0th Percentile of arr, axis = 1 : \n",       np.nanpercentile(arr, 0, axis =1, keepdims=True))

Output :

arr :
[[14, nan, 12, 33, 44], [15, nan, 27, 8, 19], [23, 2, nan, 1, 4]]

50th Percentile of arr, axis = None :  nan

50th Percentile of arr, axis = None :  14.5
0th Percentile of arr, axis = None :  1.0

50th Percentile of arr, axis = 0 :  [15.   2.  19.5  8.  19. ]
0th Percentile of arr, axis = 0 :  [14.  2. 12.  1.  4.]

50th Percentile of arr, axis = 1 :  [23.5 17.   3. ]
0th Percentile of arr, axis = 1 :  [12.  8.  1.]

0th Percentile of arr, axis = 1 :
[[23.5]
[17. ]
[ 3. ]]

0th Percentile of arr, axis = 1 :
[[12.]
[ 8.]
[ 1.]]

Code #3 :

 # Python Program illustrating # numpy.nanpercentile() method   import numpy as np   # 2D array arr = [[14, np.nan, 12, 33, 44],         [15, np.nan, 27, 8, 19],        [23, np.nan, np.nan, 1, 4,]] print("\narr : \n", arr) # Percentile along the axis = 1 print("\n50th Percentile of arr, axis = 1 : ",       np.nanpercentile(arr, 50, axis =1)) print("\n50th Percentile of arr, axis = 0 : ",       np.nanpercentile(arr, 50, axis =0))

Output :

arr :
[[14, nan, 12, 33, 44], [15, nan, 27, 8, 19], [23, nan, nan, 1, 4]]

50th Percentile of arr, axis = 1 :  [23.5 17.   4. ]

50th Percentile of arr, axis = 0 :  [15.   nan 19.5  8.  19. ]
RuntimeWarning: All-NaN slice encountered
overwrite_input, interpolation)

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