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Python | Pandas Series.update()

  • Last Updated : 29 Jan, 2019
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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.update() function modify Series in place using non-NA values from passed Series object. The function aligns on index.

Syntax: Series.update(other)

Parameter :
other: series



Returns : None

Example #1: Use Series.update() function to update the values of some cities in the given Series object




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', None, 'Toronto', 'Lisbon', 'Rio', 'Chicago', 'Lisbon'])
  
# Print the series
print(sr)

Output :

Now we will use Series.update() function to update the values identified the passed indexed in the given Series object.




# update the values at the passed index
# from the values in the passed series object
sr.update(pd.Series(['Melbourne', 'Moscow'], index = [2, 7]))

Output :

As we can see in the output, the Series.update() function has successfully updated the values in the original series object from the passed series object.

Example #2: Use Series.update() function to update the values of some elements in the given Series object




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([100, 214, 325, 88, None, 325, None, 325, 100])
  
# Print the series
print(sr)

Output :

Now we will use Series.update() function to update the values identified the passed indexed in the given Series object.




# update the values at the passed index
# from the values in the passed series object
sr.update(pd.Series([5000, 6000], index = [4, 6]))

Output :

As we can see in the output, the Series.update() function has successfully updated the values in the original series object from the passed series object.

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