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Explain how we can access elements of a Series using slicing. Give an example to support your answer.

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Remember — slicing in Series follows Python rules: start included, end excluded.
Updated On: Jul 14, 2025
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Solution and Explanation

In Pandas, slicing is a way to access a range of elements from a Series by using start and end index positions.
The syntax for slicing is similar to slicing in Python lists and arrays.
When we slice a Series, we use square brackets with start and end index: Series[start:end].
The start index is included but the end index is excluded in the result.
For example, consider a Series named s with values [5, 10, 15, 20, 25].
If we write s[1:4], it will return elements from index 1 to index 3.
So the output will be [10, 15, 20].
Slicing is useful for selecting a subset of data for further analysis.
You can also use negative indices to slice from the end of the Series.
For example, s[-3:] will return the last three elements of the Series.
Slicing keeps the index labels intact which makes it easy to work with labelled data.
In summary, slicing is a powerful feature to quickly access multiple elements from a Series without loops.
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