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Python | Pandas Series.at

  • Last Updated : 28 Jan, 2019

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.at attribute enables us to access a single value for a row/column label pair. This attribute is similar to loc, in that both provide label-based lookups.

Syntax:Series.at

Parameter : None

Returns : single value



Example #1: Use Series.at attribute to access a single value at any specific location in the given Series object.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon'])
  
# Print the series
print(sr)

Output :

Now we will use Series.at attribute to return the element present at the given index in the Series object.




# return the element at the first position
sr.at[1]

Output :

As we can see in the output, the Series.at attribute has returned ‘Chicago’ as this is the value which lies at the 1st position in the given Series object.
 
Example #2 : Use Series.at attribute to access a single value at any specific location in the given Series object.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(['Sam', 21, 'Alisa', 18, 'Sophia', 19, 'Max', 17])
  
# Print the series
print(sr)

Output :

Now we will use Series.at attribute to return the element present at the given index in the Series object.




# return the element at the first position
sr.at[5]

Output :


As we can see in the output, the Series.at attribute has returned ’19’ as this is the value which lies at the 5th position in the given Series object.

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