Drop duplicate rows in Pandas based on column 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', 'blue', '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	blue	92	Al Jennings
Omar Mullins	22	yellow	95	Omar Mullins
Spencer McDaniel	21	green	70	Spencer McDaniel

drop a duplicate row, based on column name

#here we should drop Al Jennings' record from the df, 
#since his favorite color, blue, is a duplicate with Willard Morris
df = df.drop_duplicates(subset='favorite_color', keep="first")
df

	age	favorite_color	grade	name
Willard Morris	20	blue	88	Willard Morris
Omar Mullins	22	yellow	95	Omar Mullins
Spencer McDaniel	21	green	70	Spencer McDaniel