Python | Numpy nanmedian() function
numpy.nanmedian() function can be used to calculate the median of array ignoring the NaN value. If array have NaN value and we can find out the median without effect of NaN value. Let’s see different type of examples about numpy.nanmedian() method.
Syntax: numpy.nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=)
Parameters:
a: [arr_like] input array
axis: we can use axis=1 means row wise or axis=0 means column wise.
out: output array
overwrite_input: If True, then allow use of memory of input array a for calculations. The input array will be modified by the call to median.
keepdims: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original a.
Returns: It return median in ndarray.
Example #1:
Python3
import numpy as np
arr = np.array([[ 12 , 10 , 34 ], [ 45 , 23 , np.nan]])
print ( "Shape of array is" , arr.shape)
print ( "Median of array without using nanmedian function:" ,
np.median(arr))
print ( "Using nanmedian function:" , np.nanmedian(arr))
|
Output:
Shape of array is (2, 3)
Median of array without using nanmedian function: nan
Using nanmedian function: 23.0
Example #2:
Python3
import numpy as np
arr = np.array([[ 12 , 10 , 34 ], [ 45 , 23 , np.nan]])
print ( "Shape of array is" , arr.shape)
print ( "Median of array with axis = 0:" ,
np.median(arr, axis = 0 ))
print ( "Using nanmedian function:" ,
np.nanmedian(arr, axis = 0 ))
|
Output:
Shape of array is (2, 3)
Median of array with axis = 0: [ 28.5 16.5 nan]
Using nanmedian function: [ 28.5 16.5 34. ]
Example #3:
Python3
import numpy as np
arr = np.array([[ 12 , 10 , 34 ],
[ 45 , 23 , np.nan],
[ 7 , 8 , np.nan]])
print ( "Shape of array is" , arr.shape)
print ( "Median of array with axis = 0:" ,
np.median(arr, axis = 1 ))
print ( "Using nanmedian function:" ,
np.nanmedian(arr, axis = 1 ))
|
Output:
Shape of array is (3, 3)
Median of array with axis = 0: [ 12. nan nan]
Using nanmedian function: [ 12. 34. 7.5]
Last Updated :
20 Jun, 2022
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