import seaborn
from matplotlib import pyplot

df = seaborn.load_dataset("titanic")

most_frequent_value = df["embark_town"].mode()
print("Mode: ", most_frequent_value)

df.embark_town.fillna(value=”Southampton”, inplace=True)
print(df.embark_town.isnull().mean()*100)

Here, we are using the fillna() function to fill the missing values with “Southampton.” Now, the percentage of missing values in the embark town column is zero.

Mode:  0    Southampton
Name: embark_town, dtype: object
0.0