Python | Pandas Series.hasnans

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

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.hasnans attribute returns a boolean value. It return True if the given Series object has missing values in it else it return False.

Syntax:Series.hasnans

Parameter : None

Returns : boolean

Example #1: Use Series.hasnans attribute to check if the given Series object has any missing values in it.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon'])
  
# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4'
  
# Print the series
print(sr)

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Output :

Now we will use Series.hasnans attribute to check for the missing values in sr object.

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# check for missing values.
sr.hasnans

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Output :


As we can see in the output, the Series.hasnans attribute has returned False indicating that there is no missing values in the given series object.
 
Example #2 : Use Series.hasnans attribute to check if the given Series object has any missing values in it.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([1000, 'Calgarry', 5000, None])
  
# Print the series
print(sr)

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Output :

Now we will use Series.hasnans attribute to check for the missing values in sr object.

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# check for missing values.
sr.hasnans

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Output :

As we can see in the output, the Series.hasnans attribute has returned True indicating that there is at least one missing value in the given series object.



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