numpy.nanmin () in Python

numpy.nanmin() is used when it returns the minimum value of an array or along any particular mentioned axis of the array, ignoring any Nan value.

Syntax: numpy.nanmin (arr, axis = None, out = None)
Parameters:
arr: Input array.
axis: Axis along which we want the min 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: Minimum array value (a scalar value if axis is none) or array with minimum value along specified axis.

Code # 1: Work

# Python program illustrating
# numpy.nanmin () method

 

import numpy as np

 
# 1D array

arr = [ 1 , 2 , 7 , 0 , np.nan]

print ( "arr:" , arr) 

print ( "Min of arr:" , np.amin (arr))

 
# nanmin ignores NaN values.

print ( "nanMin of arr:" , np.nanmin (arr))

Output:

 arr: [1, 2, 7, 0, nan] Min of arr: nan nanMin of arr: 0.0 

Code # 2:

# Python program illustrating
# numpy.nanm in () method

 

import numpy as np

 
# 2D array

arr = [[np.nan, 17 , 12 , 33 , 44 ], 

  [ 15 , 6 , 27 , 8 , 19 ]] 

print ( " arr: " , arr) 

 
# Minimum smoothed array

print ( "Min of arr, axis = None:" , np.nanmin (arr)) 

 
# Minimum along the first axis
# axis 0 means vertical

print ( "Min of arr, axis = 0:" , np.nanmin (arr, axis = 0 )) 

  
# Minimum along the second axis
# axis 1 means horizontal

print ( "Min of arr, axis = 1:" , np.nanmin (arr, axis = 1 )) 

Output:

 arr: [[14, 17, 12, 33, 44], [15, 6, 27, 8, 19]] Min of arr, axis = None: 6 Min of arr, axis = 0: [14 6 12 8 19] Min of arr, axis = 1: [12 6] 

Code # 3:

# Python program illustrating
# numpy.nanmin () method

 

import numpy as np

 

arr1 = np.arange ( 5

print ( " Initial arr1: " , arr1)

 
# using the out parameter

np.nanmin (arr, axis = 0 , out = arr1)

  

print ( " Changed arr1 (having results): " , arr1)

Output:

 Initial arr1: [0 1 2 3 4] Changed arr1 (having results): [14 6 12 8 19]