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.iloc attribute enables purely integer-location based indexing for selection by position over the given Series object.
Syntax:Series.iloc
Parameter : None
Returns : Series
Example #1: Use
Series.iloc attribute to perform indexing over the given Series object.
Output :
👁 Image
Now we will use
Series.iloc attribute to perform indexing over the given Series object.
Output :
👁 Image
As we can see in the output, the
Series.iloc attribute has returned a series object containing the sliced element from the original Series object.
Example #2 : Use
Series.iloc attribute to perform indexing over the given Series object.
Output :
👁 Image
Now we will use
Series.iloc attribute to perform indexing over the given Series object.
Output :
👁 Image
As we can see in the output, the
Series.iloc attribute has returned a series object containing the sliced element from the original Series object.
