pandas.isna() function in Python

This method is used to detect missing values for an array-like object. This function takes a scalar or array-like object and indicates whether values are missing (“NaN“ in numeric arrays, “None“ or “NaN“ in object arrays, “NaT“ in datetimelike).

Syntax : pandas.isna(obj)

Argument :

• obj : scalar or array-like, Object to check for null or missing values.

Below is the implementation of the above method with some examples :

Example 1 :

Python3

# importing package
import numpy
import pandas

# string "deep" is not nan value
print(pandas.isna("deep"))

# numpy.nan represents a nan value
print(pandas.isna(numpy.nan))

Output :

False
True

Example 2 :

Python3

# importing package
import numpy
import pandas

# create and view data
array = numpy.array([[1, numpy.nan, 3],
                     [4, 5, numpy.nan]])

print(array)

# numpy.nan represents a nan value
print(pandas.isna(array))

Output :

[[ 1. nan  3.]
 [ 4.  5. nan]]
[[False  True False]
 [False False  True]]