How to Add Column to Pandas Dataframe – Definitive Guide

Pandas Data frame is a two-dimensional data structure that stores data in rows and columns structure.

You can add column to pandas dataframe using the df.insert(col_index_position, “Col_Name”, Col_Values_As_List, True) statement.

In this tutorial, you’ll see different methods available to add columns to pandas dataframe.

If you’re in Hurry

You can use the below code snippet to add a new column to the pandas dataframe.

To add a column with empty values

df["new_Column"] = pd.NaT

df

To add a column with values

new_column_values = ['val1','val2','val3','val4','val5']

df["new_Column"] = new_column_values 

df

This is how you can add a new column to the pandas dataframe.

If You Want to Understand Details, Read on…

In this tutorial, you’ll learn the different methods available to add columns to the pandas dataframe. You can add columns using

• Assignment operator or the subscript notation – Use the assignment operator = to create a column in the dataframe and assign list of values.
• dataframe.insert() method – Use insert() method when you want to insert a column in a specific index position of the dataframe.
• datafame.assign() method – Use assign() method when you want to insert a column and create a new dataframe out of it rather inserting a new column in the same dataframe.

Sample Dataframe

This is the sample dataframe used throughout the tutorial.

import pandas as pd

data = {"product_name":["Keyboard","Mouse", "Monitor", "CPU", "Speakers"],
        "Unit_Price":[500,200, 5000, 10000, 250],
        "No_Of_Units":[5,5, 10, 20, 8],
       }

df = pd.DataFrame(data)

df

Dataframe Looks Like

	product_name	Unit_Price	No_Of_Units
0	Keyboard	500	5
1	Mouse	200	5
2	Monitor	5000	10
3	CPU	10000	20
4	Speakers	250	8

Let’s see the different types of adding a column to pandas dataframe.

Using Subscript Notation or Assignment operator**

You can add a column by using the = operator with a list of values.

The length of the list of values must be equal to the length of the rows in the dataframe. Otherwise, an error will be raised.

list = ['val1','val2','val3','val4','val5']

df["new_column"] = list

where,

• list = ['val1','val2','val3','val4','val5'] – creating a list with values
• df["new_column"] = list – assigning the list to the dataframe column called “new_column”.

When you execute the below code snippet, a new column called Tax_new will be added to the dataframe with values available in the list called as tax.

tax = [10,15,12,10,11]

df['Tax_new %'] = tax

df

Dataframe Looks Like

	product_name	Unit_Price	No_Of_Units	Total_Price	Tax_new %
0	Keyboard	500	5	NaT	10
1	Mouse	200	5	NaT	15
2	Monitor	5000	10	NaT	12
3	CPU	10000	20	NaT	10
4	Speakers	250	8	NaT	11

Using Insert() method

You can add a column to pandas dataframe using the insert() method available in the pandas dataframe.

Usage

• When you want to insert a column in specific position
• To avoid inserting duplicate columns with the same name. You can avoid duplicates by specifying allow_duplicates flag.

Below is the code snippet to add column using the insert() method.

# Using DataFrame.insert() to add a column
df.insert(3, "Tax%", [5,10,10,5,10], True)

df

where,

• 3 – Position where the new column needs to be inserted
• Tax% – Name of the new column
• [5,10,10,5,10] – List of values to be assigned to the new column
• True – To allow duplicate columns. If False, the new column will not be inserted if a column with name Tax% is already existing.

Dataframe Looks Like

	product_name	Unit_Price	No_Of_Units	Tax%	Total_Price	Tax_new %
0	Keyboard	500	5	5	NaT	10
1	Mouse	200	5	10	NaT	15
2	Monitor	5000	10	10	NaT	12
3	CPU	10000	20	5	NaT	10
4	Speakers	250	8	10	NaT	11

Using Assign() method

You can add a column to the pandas dataframe using the assign() method.

Usage

• When you want to create a new dataframe with the existing dataframe with additional new columns inserted.
• If you want to avoid modifications in the original dataframe.

The following code demonstrates how to use the assign() method.

df2 = df.assign(Remarks = pd.NaT)

df2

Where,

• Remarks = pd.NaT – Remarks is the column name to be inserted. pd.Nat is the values to be assigned to the new column. Note that, the column name is not enclosed with single quotes or double quotes.

Dataframe Looks Like

	product_name	Unit_Price	No_Of_Units	Tax%	Total_Price	Tax_new %	Remarks
0	Keyboard	500	5	5	NaT	10	NaT
1	Mouse	200	5	10	NaT	15	NaT
2	Monitor	5000	10	10	NaT	12	NaT
3	CPU	10000	20	5	NaT	10	NaT
4	Speakers	250	8	10	NaT	11	NaT

Add column At Specific Index

In this section, you’ll add a column at a specific position.

• Add a column at a specific index by using the df.insert() method.

Code

Use the below snippet to add a column at a specific index.

# Using DataFrame.insert() to add a column
df.insert(3, "State Tax", [5,10,10,5,10], True)

df

where,

• 3 – Position where the new column needs to be inserted
• State Tax – Name of the new column
• [5,10,10,5,10] – List of values to be assigned to the new column
• True – To allow duplicate columns. If False, the new column will not be inserted if a column with name Tax% is already existing.

An index is zero-based. Hence you’ll see the new column State Tax added in the fourth position of the dataframe.

Dataframe Looks Like

	product_name	Unit_Price	No_Of_Units	State Tax	Tax%	Total_Price	Tax_new %
0	Keyboard	500	5	5	5	NaT	10
1	Mouse	200	5	10	10	NaT	15
2	Monitor	5000	10	10	10	NaT	12
3	CPU	10000	20	5	5	NaT	10
4	Speakers	250	8	10	10	NaT	11

Dataframe Will Look like

	product_name	Unit_Price	No_Of_Units	Tax%	Total_Price
0	Keyboard	500	5	5	NaT
1	Mouse	200	5	10	NaT
2	Monitor	5000	10	10	NaT
3	CPU	10000	20	5	NaT
4	Speakers	250	8	10	NaT

You’ve learned how to add columns at a specific indexes.

Add Column to Dataframe With Constant Value

In this section, you’ll learn how to add a column to a dataframe with a constant value.

• You can do this by assigning a single value using the assignment operator as shown below.

df["Price_Increase_Col"] = 200

df

Where,

• df["Price_Increase_Col"] – specifying the new column in the dataframe.
• 200 – Constant value to be added to all the cells in the new column.

Dataframe Will Look Like

Now, a new column called Price_Increase_Col will be added to the dataframe with the value 200 in all the cells.

	product_name	Unit_Price	No_Of_Units	Tax%	Total_Price	Price_Increase_Col
0	Keyboard	500	5	5	NaT	200
1	Mouse	200	5	10	NaT	200
2	Monitor	5000	10	10	NaT	200
3	CPU	10000	20	5	NaT	200
4	Speakers	250	8	10	NaT	200

Add Multiple Columns to Dataframe

You can add multiple columns to the dataframe by using the assignment operator.

Code

df['new_column_1'], df['new_column_2'] = [constant_value_for_Col_1, constant_value_for_Col_2]

df

All the cells of the column will have the same value.

Example

You’re adding two columns Product_Category and Available_Units to the dataframe df.

df['Product_Category'], df['Available_Units'] = [pd.NaT, 3]

df

Where,

• df['Product_Category'], df['Available_Units'] – List of new columns to be added separated by comma.
• [pd.NaT, 3] – List of constant values to be added as a default value for the newly added column respectively.

Now, two new columns are added to the dataframe.

Dataframe Will Look Like

	product_name	Unit_Price	No_Of_Units	Tax%	Total_Price	Price_Increase_Col	Product_Category	Availabile_Units
0	Keyboard	500	5	5	NaT	200	NaT	3
1	Mouse	200	5	10	NaT	200	NaT	3
2	Monitor	5000	10	10	NaT	200	NaT	3
3	CPU	10000	20	5	NaT	200	NaT	3
4	Speakers	250	8	10	NaT	200	NaT	3

You’ve learned how to append multiple columns to the dataframe at once.

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