Add new column to Pandas dataframe with default value


import modules

import pandas as pd
import numpy as np

create dummy dataframe

raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
'age': [20, 19, 22, 21],
'favorite_color': ['blue', 'red', 'yellow', "green"],
'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df
age favorite_color grade name
Willard Morris 20 blue 88 Willard Morris
Al Jennings 19 red 92 Al Jennings
Omar Mullins 22 yellow 95 Omar Mullins
Spencer McDaniel 21 green 70 Spencer McDaniel

add new column to pandas dataframe with default value

#here is the simplist way to add the new column
df['My new column'] = 'default value'
df
age favorite_color grade name My new column
Willard Morris 20 blue 88 Willard Morris default value
Al Jennings 19 red 92 Al Jennings default value
Omar Mullins 22 yellow 95 Omar Mullins default value
Spencer McDaniel 21 green 70 Spencer McDaniel default value
#if you want to specify the order of the column, you can use insert
#here, we are inserting at index 1 (so should be second col in dataframe)
df.insert(1, 'My 2nd new column', 'default value 2')
df
age My 2nd new column favorite_color grade name My new column
Willard Morris 20 default value 2 blue 88 Willard Morris default value
Al Jennings 19 default value 2 red 92 Al Jennings default value
Omar Mullins 22 default value 2 yellow 95 Omar Mullins default value
Spencer McDaniel 21 default value 2 green 70 Spencer McDaniel default value


Ace your next data science interview

Get better at data science interviews by solving a few questions per week



Find a bug? Submit a suggested change on Github, or message me on Twitter.