How to remove NaN values in Python

In this article, we will learn how to remove NaN values from a Python NumPy array.

NaN values are those values that do not have a specific value associated with it.

To remove Nan values from NumPy arrays, we are using numpy.isnan() and numpy.logical_not() functions.

• numpy.isnan() – give true for all the indexes where the value is Nan.
• numpy.logical_not() – perform the logical not operation

import numpy as np 

temp = np.array([1, 6, 3, np.nan, 2, np.nan, 9, 7, np.nan])

# remove nan values 
new = temp[np.logical_not(np.isnan(temp))]

print('Original array: ', temp)

print('After removing Nan values: ', new)

# this same method can be applied
# on n-dimensional arrays

print()
# 2-D array

td = np.array([[1, 2, np.nan], [np.nan, 8, np.nan], [5, np.nan, 3]])

tdn = td[np.logical_not(np.isnan(td))]

print("Original 2D array: ", td)
print("After removing Nan values: ", tdn)

Output:

Original array:  [ 1.  6.  3. nan  2. nan  9.  7. nan]
After removing Nan values:  [1. 6. 3. 2. 9. 7.]

Original 2D array:  [[ 1.  2. nan]
 [nan  8. nan]
 [ 5. nan  3.]]
After removing Nan values:  [1. 2. 8. 5. 3.]