Python | Pandas Series.at
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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