Pandas: Check whether alpha numeric values present in a given column of a DataFrame

Last update on September 09 2025 12:40:25 (UTC/GMT +8 hours)

9. Check Alphanumeric in Column

Write a Pandas program to check whether alpha numeric values present in a given column of a DataFrame.

Note: isalnum() function returns True if all characters in the string are alphanumeric and there is at least one character, False otherwise.

Sample Solution:

Python Code :

import pandas as pd
df = pd.DataFrame({
    'name_code': ['Company','Company a001','Company 123', '1234', 'Company 12'],
    'date_of_birth ': ['12/05/2002','16/02/1999','25/09/1998','12/02/2022','15/09/1997'],
    'age': [18.5, 21.2, 22.5, 22, 23]
})
print("Original DataFrame:")
print(df)
print("\nWhether all characters in the string are alphanumeric?")
df['name_code_is_alphanumeric'] = list(map(lambda x: x.isalnum(), df['name_code']))
print(df)

Sample Output:

Original DataFrame:
      name_code date_of_birth    age
0       Company     12/05/2002  18.5
1  Company a001     16/02/1999  21.2
2   Company 123     25/09/1998  22.5
3          1234     12/02/2022  22.0
4    Company 12     15/09/1997  23.0

Whether all characters in the string are alphanumeric?
      name_code            ...            name_code_is_alphanumeric
0       Company            ...                                 True
1  Company a001            ...                                False
2   Company 123            ...                                False
3          1234            ...                                 True
4    Company 12            ...                                False

[5 rows x 4 columns]

For more Practice: Solve these Related Problems:

Write a Pandas program to verify if all values in a DataFrame column are alphanumeric using the isalnum() function.
Write a Pandas program to apply an alphanumeric check on a column and then filter the DataFrame for rows that fail the test.
Write a Pandas program to create a boolean mask indicating whether each element in a column is alphanumeric and then count the True values.
Write a Pandas program to validate alphanumeric content in a column and then replace non-alphanumeric entries with a default string.

Go to:

PREV : Find Substring with Positions.
NEXT : Check Alphabetic in Column.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.