Two seaborn plots with different scales displayed on same plot but bars overlap

Question

I am trying to include 2 seaborn countplots with different scales on the same plot but the bars display as different widths and overlap as shown below. Any idea how to get around this?

Setting dodge=False, doesn't work as the bars appear on top of each other.

Answer 1

The main problem of the approach in the question, is that the first countplot doesn't take hue into account. The second countplot won't magically move the bars of the first. An additional categorical column could be added, only taking on the 'weekend' value. Note that the column should be explicitly made categorical with two values, even if only one value is really used.

Things can be simplified a lot, just starting from the original dataframe, which supposedly already has a column 'is_weeked'. Creating the twinx ax beforehand allows to write a loop (so writing the call to sns.countplot() only once, with parameters).

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np

sns.set_style('dark')
# create some demo data
data = pd.DataFrame({'ride_hod': np.random.normal(13, 3, 1000).astype(int) % 24,
                     'is_weekend': np.random.choice(['weekday', 'weekend'], 1000, p=[5 / 7, 2 / 7])})
# now, make 'is_weekend' a categorical column (not just strings)
data['is_weekend'] = pd.Categorical(data['is_weekend'], ['weekday', 'weekend'])
fig, ax1 = plt.subplots(figsize=(16, 6))
ax2 = ax1.twinx()
for ax, category in zip((ax1, ax2), data['is_weekend'].cat.categories):
    sns.countplot(data=data[data['is_weekend'] == category], x='ride_hod', hue='is_weekend', palette='Blues', ax=ax)
    ax.set_ylabel(f'Count ({category})')
ax1.legend_.remove()  # both axes got a legend, remove one
ax1.set_xlabel('Hour of Day')
plt.tight_layout()
plt.show()