How to Remove Consecutive Duplicates in a Pandas Series?

Dropping Consecutive Duplicates in Pandas

To remove consecutive duplicates from a pandas Series, several methods can be employed.

Method 1: Using Shift

The most efficient approach is to leverage the shift() function:

a.loc[a.shift() != a]

This method compares the Series against its own shifted version, creating a boolean mask where consecutive duplicates are identified.

Method 2: Using Diff

An alternative method is to use the diff() function:

a.loc[a.diff() != 0]

However, this approach is slightly slower for large data sets.

Update:

It's important to note that using shift() with a default period of 1 is equivalent to shift(1). Therefore, the following code also produces the desired output:

a.loc[a.shift(1) != a]

By utilizing these methods, you can effectively remove consecutive duplicates from pandas Series, ensuring that only distinct values are retained.

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