Assign New Column to Pandas DataFrame

April 7, 2024

To assign a new column to Pandas DataFrame:

df = df.assign(new_column_name=["item_1", "item_2", "item_3", ...])

Case 1: Assign a Single Column to Pandas DataFrame

To start with a simple example, create a DataFrame with a single column about products:

import pandas as pd

data = {"product_name": ["tablet", "printer", "laptop", "monitor"]}

df = pd.DataFrame(data)

print(df)

This is how the DataFrame would look like in Python:

  product_name
0       tablet
1      printer
2       laptop
3      monitor

You can then use the following template to assign a new column to the DataFrame:

df = df.assign(new_column_name=["item_1", "item_2", "item_3", ...])

For example, to assign a new column, called ‘price‘, to the original DataFrame:

import pandas as pd

data = {"product_name": ["tablet", "printer", "laptop", "monitor"]}

df = pd.DataFrame(data)
df = df.assign(price=[250, 100, 1200, 300])

print(df)

Run the code in Python, and you’ll see the new column:

  product_name  price
0       tablet    250
1      printer    100
2       laptop   1200
3      monitor    300

Note that the number of items under your new column must match with the length of index in your existing DataFrame. In our example, since we have 4 products, you must add 4 prices under the new ‘price’ column. Otherwise, you’ll get the following error:

ValueError: Length of values does not match length of index

Case 2: Assign Multiple Columns to Pandas DataFrame

Now let’s assign two columns to the DataFrame:

  • The ‘price‘ column; and
  • The ‘brand‘ column

You can then apply the following code in order to assign those two columns to the DataFrame:

import pandas as pd

data = {"product_name": ["tablet", "printer", "laptop", "monitor"]}

df = pd.DataFrame(data)
df = df.assign(price=[250, 100, 1200, 300], brand=["aa", "bb", "cc", "dd"])

print(df)

Once you run the code in Python, you’ll see these two additional columns:

  product_name  price  brand
0       tablet    250     aa
1      printer    100     bb
2       laptop   1200     cc
3      monitor    300     dd

You can read more about assigning new columns to a DataFrame by visiting the Pandas Documentation.