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import seaborn as sns
import pandas as pd

# Load the dataset
df = sns.load_dataset("titanic")

# 1. Identify missing values
print(f"Missing in 'embarked': {df['embarked'].isnull().sum()}")
print(f"Missing in 'embark_town': {df['embark_town'].isnull().sum()}")

# 2. Find the mode (most common value)
embarked_mode = df['embarked'].mode()[0]          # Usually 'S'
embark_town_mode = df['embark_town'].mode()[0]    # Usually 'Southampton'

# 3. Fill the missing values
df['embarked'] = df['embarked'].fillna(embarked_mode)
df['embark_town'] = df['embark_town'].fillna(embark_town_mode)

# Verify
print("\nAfter handling missing values:")
print(df[['embarked', 'embark_town']].isnull().sum())