Adding new column to existing DataFrame in Pandas

Let’s discuss how to add new columns to the existing DataFrame in Pandas. There are multiple ways we can do this task.

Method #1: By declaring a new list as a column. 

Python3

# Import pandas package
import pandas as pd

# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Height': [5.1, 6.2, 5.1, 5.2],
        'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}

# Convert the dictionary into DataFrame
df = pd.DataFrame(data)

# Declare a list that is to be converted into a column
address = ['Delhi', 'Bangalore', 'Chennai', 'Patna']

# Using 'Address' as the column name
# and equating it to the list
df['Address'] = address

# Observe the result
print(df)

Output:

Note that the length of your list should match the length of the index column otherwise it will show an error. 

Method #2: By using DataFrame.insert()

It gives the freedom to add a column at any position we like and not just at the end. It also provides different options for inserting the column values.

Example

Python3

# Import pandas package
import pandas as pd

# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Height': [5.1, 6.2, 5.1, 5.2],
        'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}

# Convert the dictionary into DataFrame
df = pd.DataFrame(data)

# Using DataFrame.insert() to add a column
df.insert(2, "Age", [21, 23, 24, 21], True)

# Observe the result
print(df)

Output:

Method #3: Using Dataframe.assign() method

This method will create a new dataframe with a new column added to the old dataframe.

Example

Python3

# Import pandas package
import pandas as pd

# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Height': [5.1, 6.2, 5.1, 5.2],
        'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}


# Convert the dictionary into DataFrame
df = pd.DataFrame(data)

# Using 'Address' as the column name and equating it to the list
df2 = df.assign(address=['Delhi', 'Bangalore', 'Chennai', 'Patna'])

# Observe the result
print(df2)

Output:

Method #4: By using a dictionary

We can use a Python dictionary to add a new column in pandas DataFrame. Use an existing column as the key values and their respective values will be the values for a new column.

Example

Python3

# Import pandas package
import pandas as pd

# Define a dictionary containing Students data
data = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Height': [5.1, 6.2, 5.1, 5.2],
        'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}

# Define a dictionary with key values of
# an existing column and their respective
# value pairs as the # values for our new column.
address = {'Delhi': 'Jai', 'Bangalore': 'Princi',
           'Patna': 'Gaurav', 'Chennai': 'Anuj'}

# Convert the dictionary into DataFrame
df = pd.DataFrame(data)

# Provide 'Address' as the column name
df['Address'] = address

# Observe the output
print(df)

Output: