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