Which code snippet correctly loads a dataset, checks for missing values, and fills them with the mean for all numerical columns?
import pandas as pddf = pd.read_csv('data.csv')df.replace(to_replace=None, value=df.mean(), inplace=True)
import pandas as pddf = pd.read_csv('data.csv')for column in df.columns: df[column].fillna(df[column].mean(), inplace=True)
import pandas as pddf = pd.read_csv('data.csv')df.dropna(inplace=True)df.fillna(df.mean(), inplace=True)
import pandas as pddf = pd.read_csv('data.csv')if df.isnull().sum().any(): df.fillna(df.mean(), inplace=True)