You can use the following methods to filter a pandas DataFrame where a column is not equal to specific values:

**Method 1: Filter where Column is Not Equal to One Specific Value**

#filter rows where team column is not equal to 'Nets' df_filtered = df[df['team'] != 'Nets']

**Method 2: Filter where Column is Not Equal to Several Specific Values**

#filter rows where team column is not equal to 'Nets', 'Mavs' or 'Kings'df_filtered = df[~df['team'].isin(['Nets', 'Mavs', 'Kings'])]

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['Mavs', 'Mavs', 'Nets', 'Nets', 'Heat', 'Heat', 'Kings'], 'points': [22, 28, 35, 34, 29, 28, 23]}) #view DataFrame print(df) team points 0 Mavs 22 1 Mavs 28 2 Nets 35 3 Nets 34 4 Heat 29 5 Heat 28 6 Kings 23

**Example 1: Filter where Column is Not Equal to One Specific Value**

We can use the following syntax to filter the DataFrame to only contain rows where the **team** column is not equal to ‘Nets’:

#filter rows where team column is not equal to 'Nets' df_filtered = df[df['team'] != 'Nets'] #view filtered DataFrame print(df_filtered) team points 0 Mavs 22 1 Mavs 28 4 Heat 29 5 Heat 28 6 Kings 23

Notice that each row where the **team** name was ‘Nets’ has been filtered out of the DataFrame.

**Note**: The symbol **!=** represents “not equal” in pandas.

**Example 2: Filter where Column is Not Equal to Several Specific Values**

We can use the following syntax to filter the DataFrame to only contain rows where the **team** column is not equal to ‘Nets’, ‘Mavs’ or ‘Kings’:

#filter rows where team column is not equal to 'Nets', 'Mavs' or 'Kings'df_filtered = df[~df['team'].isin(['Nets', 'Mavs', 'Kings'])] #view filtered DataFrame print(df_filtered) team points 4 Heat 29 5 Heat 28

Notice that each row where the **team** name was ‘Nets’, ‘Mavs’ or ‘Kings’ has been filtered out of the DataFrame.

**Note**: The symbol **~** represents “not” in pandas.

**Documentation**: You can find the complete documentation for the pandas **isin()** function here.

**Additional Resources**

The following tutorials explain how to perform other common tasks in pandas:

Pandas: How to Add Filter to Pivot Table

Pandas: How to Filter for “Not Contains”

Pandas: How to Filter Rows that Contain a Specific String