How to Add New Column to Existing DataFrame in Python Pandas

Ahmed Waheed Feb 02, 2024 Pandas
  1. [] Operator Method to Add a New Column in Pandas
  2. df.insert() Method to Add New Column in Pandas
  3. df.assign() Method to Add New Column in Pandas
  4. df.loc() Method to Add New Column in Pandas
How to Add New Column to Existing DataFrame in Python Pandas

Adding a new column to existing DataFrame is used very frequently when working with large data sets. For example, the existing DataFrame has First, Last, and Age columns, and we need to add a new column city to it. Listed below are the different ways to achieve this task.

  1. [] operator Method
  2. df.insert() Method
  3. df.assign() Method
  4. df.loc() Method

We will use the same DataFrame in the next sections as follows,

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])
print(df)

Output:

     First      Last Age
0      Ali     Azmat  30
1  Sharukh      Khan  40
2    Linus  Torvalds  70

[] Operator Method to Add a New Column in Pandas

We could use the [] operator to add a new column to the existing DataFrame.

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])
city = ["Lahore", "Dehli", "New York"]
df["city"] = city
print(df)

Output:

     First      Last Age      city
0      Ali     Azmat  30    Lahore
1  Sharukh      Khan  40     Dehli
2    Linus  Torvalds  70  New York

df.insert() Method to Add New Column in Pandas

You can use df.insert() function if you want to add the new column at a specific index. The first parameter of df.insert() function is the insertion index starting from zero.

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])
df.insert(3, "city", ["Lahore", "Dehli", "New York"], True)
print(df)

Output:

     First      Last Age      city
0      Ali     Azmat  30    Lahore
1  Sharukh      Khan  40     Dehli
2    Linus  Torvalds  70  New York

df.assign() Method to Add New Column in Pandas

df.assign() can also be used to add a new column to an existing DataFrame.

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])

df = df.assign(city=["Lahore", "Dehli", "New York"])
print(df)

Output:

     First      Last Age      city
0      Ali     Azmat  30    Lahore
1  Sharukh      Khan  40     Dehli
2    Linus  Torvalds  70  New York

Let’s see how to add multiple columns using df.assign(). The below example will add city and score columns.

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])

df = df.assign(city=["Lahore", "Dehli", "New York"], score=[20, 30, 40])
print(df)

Output:

     First      Last Age      city  score
0      Ali     Azmat  30    Lahore     20
1  Sharukh      Khan  40     Dehli     30
2    Linus  Torvalds  70  New York     40

df.loc() Method to Add New Column in Pandas

df.loc() method can also add a new column into an existing DataFrame.

import pandas as pd

data = [["Ali", "Azmat", "30"], ["Sharukh", "Khan", "40"], ["Linus", "Torvalds", "70"]]
df = pd.DataFrame(data, columns=["First", "Last", "Age"])
df.loc[:, "city"] = ["Lahore", "Dehli", "New York"]
print(df)

Output:

     First      Last Age      city
0      Ali     Azmat  30    Lahore
1  Sharukh      Khan  40     Dehli
2    Linus  Torvalds  70  New York
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