To begin discussing the methods of filtering series, it’s important to ensure that you have a clear understanding of what Series are. If you’re not familiar with this data structure, you can check out the Building Pandas series with several datatypes thread to gain a comprehensive understanding of what Series are and how they can be created. Let us now delve into each filtering method and provide examples to illustrate their use.

#### 1. Using a "for" loop:

This method however is slower than the others which are listed below as in this method, each element is individually iterated and then compared with the other series `series2`

to check if it is present in this series or not.

#### 2. Using the "isin()" method:

- The
`isin()`

method is used to check whether each element in a Pandas DataFrame or Series is contained in a sequence of values which in our case is another series. - It returns a boolean mask indicating which values are in the sequence of values passed to the method.

The use of `~`

negates the results obtained using `isin()`

, the values which were present in `series2`

now have a `False`

and the values not in `series2`

have a `True`

and we use this boolean mask to filter `series1`

getting those values which were only in `series1`

.

#### 3. Using set "subtraction" operator:

#### 4. Using set "difference()" method:

- The
`difference()`

method is a method in Python that is used to get the set difference of two sets. - It returns a set containing elements present in the first set but not in the second set.