You can use the following methods to check if a particular value exists in a column of a pandas DataFrame:

Method 1: Check if One Value Exists in Column

22 in df['my_column'].values

Method 2: Check if One of Several Values Exist in Column

df['my_column'].isin([44, 45, 22]).any()

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

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'points': [18, 22, 19, 14, 14, 11, 20, 28],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})

#view DataFrame
print(df)

  team  points  assists  rebounds
0    A      18        5        11
1    B      22        7         8
2    C      19        7        10
3    D      14        9         6
4    E      14       12         6
5    F      11        9         5
6    G      20        9         9
7    H      28        4        12

Example 1: Check if One Value Exists in Column

The following code shows how to check if the value 22 exists in the points column:

#check if 22 exists in the 'points' column
22 in df['points'].values

True

The output returns True, which tells us that the value 22 does exist in the points column.

We can use the same syntax with string columns as well.

For example, the following code shows how to check if the string ‘J’ exists in the team column:

#check if 'J' exists in the 'team' column
'J' in df['team'].values

False

The output returns False, which tells us that the string ‘J’ does not exist in the team column.

Example 2: Check if One of Several Values Exist in Column

The following code shows how to check if any of the values in the list [44, 45, 22] exist in the points column:

#check if 44, 45 or 22 exist in the 'points' column
df['points'].isin([44, 45, 22]).any()

True

The output returns True, which tells us that at least one of the values in the list [44, 45, 22] exists in the points column of the DataFrame.

We can use the same syntax with string columns as well.

For example, the following code shows how to check if any string in the list [‘J’, ‘K’, ‘L’] exists in the team column:

#check if J, K, or L exists in the 'team' column
df['team'].isin(['J', 'K', 'L']).any() 
False

The output returns False, which tells us that none of the strings in the list exist in the team column.

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