fig, ax = plt.subplots(figsize=(4,3))
sns.countplot(data=train_dt, x='Pclass', ax=ax)
abs_values = train_dt['Pclass'].value_counts()
rel_values = train_dt['Pclass'].value_counts(normalize=True).values * 100
lbls = [f'{p[0]} ({p[1]:.0f}%)' for p in zip(abs_values, rel_values)]
ax.bar_label(ax.containers[0], label_type='edge', labels=lbls)
plt.show()
When you run the code above, the graph will look like the one below.
The values themselves aren't wrong, but the graph and labels don't match.
What did I do wrong?
First, a word of thanks.