Home » Pandas: How to Create New DataFrame from Existing DataFrame

Pandas: How to Create New DataFrame from Existing DataFrame

by Tutor Aspire

There are three common ways to create a new pandas DataFrame from an existing DataFrame:

Method 1: Create New DataFrame Using Multiple Columns from Old DataFrame

new_df = old_df[['col1','col2']].copy()

Method 2: Create New DataFrame Using One Column from Old DataFrame

new_df = old_df[['col1']].copy()

Method 3: Create New DataFrame Using All But One Column from Old DataFrame

new_df = old_df.drop('col1', axis=1)

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

import pandas as pd

#create DataFrame
old_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, 7, 9, 12]})

#view DataFrame
print(old_df)

Example 1: Create New DataFrame Using Multiple Columns from Old DataFrame

The following code shows how to create a new DataFrame using multiple columns from the old DataFrame:

#create new DataFrame from existing DataFrame
new_df = old_df[['points','rebounds']].copy()

#view new DataFrame
print(new_df)

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

#check data type of new DataFrame
type(new_df)

pandas.core.frame.DataFrame

Notice that this new DataFrame only contains the points and rebounds columns from the old DataFrame.

Note: It’s important to use the copy() function when creating the new DataFrame so that we avoid any SettingWithCopyWarning if we happen to modify the new DataFrame in any way.

Example 2: Create New DataFrame Using One Column from Old DataFrame

The following code shows how to create a new DataFrame using one column from the old DataFrame:

#create new DataFrame from existing DataFrame
new_df = old_df[['points']].copy()

#view new DataFrame
print(new_df)

   points
0      18
1      22
2      19
3      14
4      14
5      11
6      20
7      28

#check data type of new DataFrame
type(new_df)

pandas.core.frame.DataFrame

Notice that this new DataFrame only contains the points and column from the old DataFrame.

Example 3: Create New DataFrame Using All But One Column from Old DataFrame

The following code shows how to create a new DataFrame using all but one column from the old DataFrame:

#create new DataFrame from existing DataFrame
new_df = old_df.drop('points', axis=1)

#view new DataFrame
print(new_df)

  team  assists  rebounds
0    A        5        11
1    A        7         8
2    A        7        10
3    A        9         6
4    B       12         6
5    B        9         7
6    B        9         9
7    B        4        12

#check data type of new DataFrame
type(new_df)

pandas.core.frame.DataFrame

Notice that this new DataFrame contains all of the columns from the original DataFrame except the points column.

Additional Resources

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

How to Create Empty Pandas DataFrame with Column Names
How to Add a Column to a Pandas DataFrame
How to Add Multiple Columns to Pandas DataFrame

You may also like