You can use the following methods to filter the values in a pandas Series:

**Method 1: Filter Values Based on One Condition**

#filter for values equal to 7 my_series.loc[lambda x : x == 7]

**Method 2: Filter Values Using “OR” Condition**

#filter for values less than 10orgreater than 20 my_series.loc[lambda x : (x < 10) | (x > 20)]

**Method 3: Filter Values Using “AND” Condition**

#filter for values greater than 10andless than 20 my_series.loc[lambda x : (x > 10) & (x < 20)]

**Method 4: Filter Values Contained in List**

#filter for values that are equal to 4, 7, or 23 my_series[my_series.isin([4, 7, 23])]

This tutorial explains how to use each method in practice with the following pandas Series:

**import pandas as pd
#create pandas Series
data = pd.Series([4, 7, 7, 12, 19, 23, 25, 30])
#view pandas Series
print(data)
0 4
1 7
2 7
3 12
4 19
5 23
6 25
7 30
dtype: int64**

**Example 1: Filter Values Based on One Condition**

The following code shows how to filter the pandas Series for values equal to 7:

#filter for values equal to 7 data.loc[lambda x : x == 7] 1 7 2 7 dtype: int64

We can also filter for values **not equal** to 7:

#filter for values not equal to 7 data.loc[lambda x : x != 7] 0 4 3 12 4 19 5 23 6 25 7 30 dtype: int644

**Example 2: Filter Values Using “OR” Condition**

The following code shows how to filter the pandas Series for values less than 10 **or** greater than 20:

#filter for values less than 10orgreater than 20 data.loc[lambda x : (x < 10) | (x > 20)] 0 4 1 7 2 7 5 23 6 25 7 30 dtype: int64

**Example 3: Filter Values Using “AND” Condition**

The following code shows how to filter the pandas Series for values greater than 10 **and** less than 20:

#filter for values greater than 10andless than 20 data.loc[lambda x : (x > 10) & (x < 20)] 3 12 4 19 dtype: int64

**Example 4: Filter Values Contained in List**

The following code shows how to filter the pandas Series for values that are contained in a list:

#filter for values that are equal to 4, 7, or 23 data[data.isin([4, 7, 23])] 0 4 1 7 2 7 5 23 dtype: int64

**Additional Resources**

The following tutorials explain how to perform other common filtering operations in Python:

How to Filter Pandas DataFrame Rows that Contain a Specific String

How to Filter a Pandas DataFrame on Multiple Conditions

How to Use “NOT IN” Filter in Pandas DataFrame