[Python] How to adjust size of violin plot based on number of hues available for each category?

I need to create a violin plot based on two categories. But, some of the combination of categories are not available in the data. So it creates a white space, when i try to make the plot. I remember long ago i was able to adjust the size of the violins when the categories were not available in r using geom_violin(position= position_dodge(0.9)) refer to the attached image. Now i need to create a similar figure with python but when i try to make violin plot using seaborn i get whitespace when certain combinations of variables arent available (see image). Following is the code I am using in python. I would appreciate any help with this.

Reproducible example

import numpy as np

# Define categories for Depth and Hydraulic Conductivity
depth_categories = ["<0.64", "0.64-0.82", "0.82-0.90", ">0.9"]
hydraulic_conductivity_categories = ["<0.2", "0.2-2.2", "2.2-15.5", ">15.5"]

# Generate random HSI values
np.random.seed(42) # For reproducibility
hsi_values = np.random.uniform(low=0, high=35, size=30)

# Generate random categories for Depth and Hydraulic Conductivity
depth_values = np.random.choice(depth_categories, size=30)
hydraulic_conductivity_values = np.random.choice(hydraulic_conductivity_categories, size=30)

# Ensure not all combinations are available by removing some combinations
for i in range(5):
depth_values = depth_categories[i % len(depth_categories)]
hydraulic_conductivity_values = hydraulic_conductivity_categories[(i + 1) % len(hydraulic_conductivity_categories)]

# Create the DataFrame
dummy_data = pd.DataFrame({
'HSI': hsi_values,
'Depth': depth_values,
'Hydraulic_Conductivity': hydraulic_conductivity_values
})
# Violin plot for Soil Depth and Hydraulic Conductivity
plt.figure(figsize=(12, 6))
sns.violinplot(x='Depth', y='HSI', hue='Hydraulic_Conductivity', data=dummy_data, palette=color_palette,
density_norm="count",
cut = 0,
gap = 0.1,
linewidth=0.5,
common_norm=False,
dodge=True)
plt.xlabel("DDDD")
plt.ylabel("XXX")
plt.title("Violin plot of XXX by YYYY and DDDD")
plt.ylim(-5, 35)
plt.legend(title='DDDD', loc='upper right')
# sns.despine()# Remove the horizontal lines
plt.show()




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