Let’s discuss how to add new columns to existing DataFrame in Pandas. There are multiple ways we can do this task.
Method #1: By declaring a new list as a column.
# Import pandas package import pandas as pd # Define a dictionary containing Students datadata = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], 'Height': [5.1, 6.2, 5.1, 5.2], 'Qualification': ['Msc', 'MA', 'Msc', 'Msc']} # Convert the dictionary into DataFramedf = pd.DataFrame(data) # Declare a list that is to be converted into a columnaddress = ['Delhi', 'Bangalore', 'Chennai', 'Patna'] # Using 'Address' as the column name# and equating it to the listdf['Address'] = address # Observe the resultdf |
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.
# Import pandas package import pandas as pd # Define a dictionary containing Students datadata = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], 'Height': [5.1, 6.2, 5.1, 5.2], 'Qualification': ['Msc', 'MA', 'Msc', 'Msc']} # Convert the dictionary into DataFramedf = pd.DataFrame(data) # Using DataFrame.insert() to add a columndf.insert(2, "Age", [21, 23, 24, 21], True) # Observe the resultdf |
Output:
Method #3: Using Dataframe.assign() method
This method will create a new dataframe with new column added to the old dataframe.
# Import pandas package import pandas as pd # Define a dictionary containing Students datadata = {'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], 'Height': [5.1, 6.2, 5.1, 5.2], 'Qualification': ['Msc', 'MA', 'Msc', 'Msc']} # Convert the dictionary into DataFramedf = pd.DataFrame(data) # Using 'Address' as the column name and equating it to the listdf2 = df.assign(address = ['Delhi', 'Bangalore', 'Chennai', 'Patna']) # Observe the resultdf2 |
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 new column.
# Import pandas package import pandas as pd # Define a dictionary containing Students datadata = {'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 DataFramedf = pd.DataFrame(data) # Provide 'Address' as the column namedf['Address'] = address # Observe the outputdf |
Output:
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