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’.

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