Open In App

numpy.nanpercentile() in Python

Last Updated : 09 Aug, 2022
Improve
Improve
Like Article
Like
Save
Share
Report

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




# Python Program illustrating
# numpy.nanpercentile() method
   
import numpy as np
   
# 1D array
arr = [20, 2, 7, np.nan, 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))
 
print("\n50th 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]
50th percentile of arr :  nan
25th percentile of arr :  nan
75th percentile of arr :  nan

50th percentile of arr :  13.5
25th percentile of arr :  5.75
75th percentile of arr :  23.5

  Code #2 : 

Python




# 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(& quot
       \narr: \n"
       , arr)
 
# Percentile of the flattened array
print(& quot
       \n50th Percentile of arr, axis = None : & quot
       ,
       np.percentile(arr, 50))
print(& quot
       \n50th Percentile of arr, axis = None : & quot
       ,
       np.nanpercentile(arr, 50))
print(& quot
       0th Percentile of arr, axis = None : & quot
       ,
       np.nanpercentile(arr, 0))
 
# Percentile along the axis = 0
print(& quot
       \n50th Percentile of arr, axis = 0 : & quot
       ,
       np.nanpercentile(arr, 50, axis=0))
print(& quot
       0th Percentile of arr, axis = 0 : & quot
       ,
       np.nanpercentile(arr, 0, axis=0))
 
# Percentile along the axis = 1
print(& quot
       \n50th Percentile of arr, axis = 1 : & quot
       ,
       np.nanpercentile(arr, 50, axis=1))
print(& quot
       0th Percentile of arr, axis = 1 : & quot
       ,
       np.nanpercentile(arr, 0, axis=1))
 
print(& quot
       \n0th Percentile of arr, axis = 1: \n"
       ,
       np.nanpercentile(arr, 50, axis=1, keepdims=True))
print(& quot
       \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




# 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(& quot
       \narr: \n"
       , arr)
# Percentile along the axis = 1
print(& quot
       \n50th Percentile of arr, axis = 1 : & quot
       ,
       np.nanpercentile(arr, 50, axis=1))
print(& quot
       \n50th Percentile of arr, axis = 0 : & quot
       ,
       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)


Like Article
Suggest improvement
Share your thoughts in the comments

Similar Reads