Pandas: How to Add String to Each Value in Column

You can use the following methods to add a string to each value in a column of a pandas DataFrame:

Method 1: Add String to Each Value in Column

df['my_column'] = 'some_string' + df['my_column'].astype(str)

Method 2: Add String to Each Value in Column Based on Condition

#define condition
mask = (df['my_column'] == 'A')

#add string to values in column equal to 'A'
df.loc[mask, 'my_column'] = 'some_string' + df['my_column'].astype(str)

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': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],
                   '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    A      22        7         8
2    A      19        7        10
3    A      14        9         6
4    B      14       12         6
5    B      11        9         5
6    B      20        9         9
7    B      28        4        12

Example 1: Add String to Each Value in Column

The following code shows how to add the string ‘team_’ to each value in the team column:

#add string 'team_' to each value in team column
df['team'] = 'team_' + df['team'].astype(str)

#view updated DataFrame
print(df)

     team  points  assists  rebounds
0  team_A      18        5        11
1  team_B      22        7         8
2  team_C      19        7        10
3  team_D      14        9         6
4  team_E      14       12         6
5  team_F      11        9         5
6  team_G      20        9         9
7  team_H      28        4        12

Notice that the prefix ‘team_’ has been added to each value in the team column.

You can also use the following syntax to instead add ‘_team’ as a suffix to each value in the team column:

#add suffix 'team_' to each value in team column
df['team'] = df['team'].astype(str) + '_team'

#view updated DataFrame
print(df)

     team  points  assists  rebounds
0  A_team      18        5        11
1  A_team      22        7         8
2  A_team      19        7        10
3  A_team      14        9         6
4  B_team      14       12         6
5  B_team      11        9         5
6  B_team      20        9         9
7  B_team      28        4        12

Example 2: Add String to Each Value in Column Based on Condition

The following code shows how to add the prefix ‘team_’ to each value in the team column where the value is equal to ‘A’:

#define condition
mask = (df['team'] == 'A')

#add string 'team_' to values that meet the condition
df.loc[mask, 'team'] = 'team_' + df['team'].astype(str)

#view updated DataFrame
print(df)

     team  points  assists  rebounds
0  team_A      18        5        11
1  team_A      22        7         8
2  team_A      19        7        10
3  team_A      14        9         6
4       B      14       12         6
5       B      11        9         5
6       B      20        9         9
7       B      28        4        12

Notice that the prefix ‘team_’ has only been added to the values in the team column whose value was equal to ‘A’.

Additional Resources

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

Pandas: How to Select Columns Containing a Specific String
Pandas: How to Select Rows that Do Not Start with String
Pandas: How to Check if Column Contains String