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