Pandas – Add Column From Another Dataframe

In this tutorial, we will look at how to add a column to a pandas dataframe from another column with the help of some examples.

How to add a new column from another dataframe in Pandas?

Let’s say your dataframe, df1 has columns “A” and “B” and there is another dataframe, df2 having columns “C”, “D”, and “E”. You want to add column “C” to the dataframe df1 (assuming both the dataframes have the same length).

The following is the syntax –

# add column "C" to df1 from df2
df1["C"] = df2["C"]

This will add column “C” to the end of the dataframe df1. If you want to add the new column at a specific column position, use the pandas dataframe insert() function.

Note that here we are simply creating a new column and setting its values to the values from a column in another dataframe. If you want to add a column based on a matching key (performing a join operation) use the pandas join() function instead.

Examples

Let’s now look at some examples of using the above syntax.

First, we will create some dataframes that we will use throughout this tutorial.

import pandas as pd

# employee name and age data
data1 = {
    "Name": ["Jim", "Dwight", "Angela", "Tobi"],
    "Age": [26, 28, 27, 32]
}
# employee department and salary data
data2 = {
    "Department": ["Sales", "Sales", "Accounting", "HR"],
    "Salary": [55000, 60000, 52000, 45000]
}

# create pandas dataframe
df1 = pd.DataFrame(data1)
# create pandas dataframe
df2 = pd.DataFrame(data2)

# display the dataframe
print(df1)
print("--------------")
print(df2)

Output:

     Name  Age
0     Jim   26
1  Dwight   28
2  Angela   27
3    Tobi   32
--------------
   Department  Salary
0       Sales   55000
1       Sales   60000
2  Accounting   52000
3          HR   45000

Here, we create two dataframes – df1 and df2. The dataframe df1 contains the “Name” and “Age” information of some employees in an office and the dataframe df2 contains the “Department” and “Salary” information.

Example 1 – Add column from another dataframe using the assignment operator =

Let’s add the “Department” to the dataframe df1 from the dataframe df2.

# add "Department" column to df1 from df2
df1["Department"] = df2["Department"]
# display df1
df1

Output:

The dataframe df1 now has the “Department” column. Note that both the dataframes df1 and df2 have the same lengths and we’re assuming that the values at the same row indices correspond to the same entity (in this example, the same employee).

Example 2 – Add column from another dataframe using insert() function

In the above example, the new column was added at the end of the dataframe. If you want to add the new column at a specific column position, use the pandas dataframe insert() function.

The following is the syntax –

df.insert(loc, column, value, allow_duplicates=False)

We pass the insertion index, column name, and column values to the insert() function. Note that this function modifies the dataframe in place.

Let’s add the “Department” column to the original df1 dataframe at index 1.

# reset df1 and df2 to their original values
df1 = pd.DataFrame(data1)
df2 = pd.DataFrame(data2)

# add "Department" column to df1 (from df2) at index 1
df1.insert(1, "Department", df2["Department"])
# display df1
df1

Output:

You can see that the “Department” column from the dataframe df2 is added to the dataframe df1 at index 1.

Summary

In this tutorial, we looked at how to add a new column to a dataframe from another dataframe. The following are the key takeaways –

• The idea is to create a new column and set its values to the values of the column in another dataframe (assuming both the dataframes have the same length).
• To add the new column at a specific column position, use the pandas dataframe insert() function instead.

You might also be interested in –

• Pandas – Add Column to Existing DataFrame
• Pandas – Add an Empty Column to a DataFrame
• Pandas – Join vs Merge
• Understanding Joins in Pandas
• Pandas – Merge DataFrames on Multiple Columns