Home » How to Add Empty Column to Pandas DataFrame (3 Examples)

How to Add Empty Column to Pandas DataFrame (3 Examples)

by Erma Khan

You can use the following methods to add empty columns to a pandas DataFrame:

Method 1: Add One Empty Column with Blanks

df['empty_column'] = ""

Method 2: Add One Empty Column with NaN Values

df['empty_column'] = np.nan

Method 3: Add Multiple Empty Columns with NaN Values

df[['empty1', 'empty2', 'empty3']] = np.nan

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 Empty Column with Blanks

The following code shows how to add one empty column with all blank values:

#add empty column
df['blanks'] = ""

#view updated DataFrame
print(df)

  team  points  assists blanks
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   

The new column called blanks is filled with blank values.

Example 2: Add One Empty Column with NaN Values

The following code shows how to add one empty column with all NaN values:

import numpy as np

#add empty column with NaN values
df['empty'] = np.nan

#view updated DataFrame
print(df)

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

The new column called empty is filled with NaN values.

Example 3: Add Multiple Empty Columns with NaN Values

The following code shows how to add multiple empty columns with all NaN values:

import numpy as np

#add three empty columns with NaN values
df[['empty1', 'empty2', 'empty3']] = np.nan

#view updated DataFrame
print(df)

  team  points  assists  empty1  empty2  empty3
0    A      18        5     NaN     NaN     NaN
1    B      22        7     NaN     NaN     NaN
2    C      19        7     NaN     NaN     NaN
3    D      14        9     NaN     NaN     NaN
4    E      14       12     NaN     NaN     NaN
5    F      11        9     NaN     NaN     NaN
6    G      20        9     NaN     NaN     NaN
7    H      28        4     NaN     NaN     NaN

Notice that all three of the new columns are filled with NaN values.

Additional Resources

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

How to Rename Columns in Pandas
How to Add a Column to a Pandas DataFrame
How to Change the Order of Columns in Pandas DataFrame

Related Posts