Python | Pandas Series.isnull()
Last Updated :
12 Feb, 2019
Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.isnull()
function detect missing values in the given series object. It return a boolean same-sized object indicating if the values are NA. Missing values gets mapped to True
and non-missing value gets mapped to False
.
Syntax: Series.isnull()
Parameter : None
Returns : boolean
Example #1: Use Series.isnull()
function to detect missing values in the given series object.
import pandas as pd
sr = pd.Series([ 10 , 25 , 3 , 25 , 24 , 6 ])
index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ]
sr.index = index_
print (sr)
|
Output :
Now we will use Series.isnull()
function to detect all the missing values in the given series object.
result = sr.isnull()
print (result)
|
Output :
As we can see in the output, the Series.isnull()
function has returned an object containing boolean values. All values have been mapped to False
because there is no missing value in the given series object.
Example #2 : Use Series.isnull()
function to detect missing values in the given series object.
import pandas as pd
sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , None , 32 , 10 , 5 , 24 , None ])
index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' )
sr.index = index_
print (sr)
|
Output :
Now we will use Series.isnull()
function to detect all the missing values in the given series object.
result = sr.isnull()
print (result)
|
Output :
As we can see in the output, the Series.isnull()
function has returned an object containing boolean values. All missing values have been mapped to True
.
Share your thoughts in the comments
Please Login to comment...