You can use the following methods to add a column with a constant value to a pandas DataFrame:

Method 1: Add One Column with Constant Value

df['new'] = 5

Method 2: Add Multiple Columns with Same Constant Value

df[['new1', 'new2', 'new3']] = 5

Method 3: Add Multiple Columns with Different Constant Values

#define dictionary of new values
new_constants = {'new1': 5, 'new2': 10, 'new3': 15}

#add multiple columns with different constant values
df = df.assign(**new_constants)

The following examples show how to use each method with the following pandas DataFrames:

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]})

#view DataFrame
print(df)

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

Example 1: Add One Column with Constant Value

The following code shows how to add one column with a value of 5 for each row:

#add column with constant value
df['new'] = 5

#view updated DataFrame
print(df)

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

The new column called new is filled with the constant value of 5 for each row.

Example 2: Add Multiple Columns with Same Constant Value

The following code shows how to add multiple columns that all have the same constant value of 5:

#add three new columns each with a constant value of 5
df[['new1', 'new2', 'new3']] = 5

#view updated DataFrame
print(df)

  team  points  assists  new1  new2  new3
0    A      18        5     5     5     5
1    B      22        7     5     5     5
2    C      19        7     5     5     5
3    D      14        9     5     5     5
4    E      14       12     5     5     5
5    F      11        9     5     5     5
6    G      20        9     5     5     5
7    H      28        4     5     5     5

Notice that each new column contains the value 5 in each row.

Example 3: Add Multiple Columns with Different Constant Values

The following code shows how to add multiple columns with different constant values:

#define dictionary of new values
new_constants = {'new1': 5, 'new2': 10, 'new3': 15}

#add multiple columns with different constant values
df = df.assign(**new_constants)

#view updated DataFrame
print(df)

  team  points  assists  new1  new2  new3
0    A      18        5     5    10    15
1    B      22        7     5    10    15
2    C      19        7     5    10    15
3    D      14        9     5    10    15
4    E      14       12     5    10    15
5    F      11        9     5    10    15
6    G      20        9     5    10    15
7    H      28        4     5    10    15

Notice that each of the three new columns have a different constant value.

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

How to Add Empty Column to Pandas DataFrame