import matplotlib.pyplot as plt

import seaborn as sns

import pandas as pd

import numpy as np

prob = np.random.rand(7) + 0.1

prob /= prob.sum()

df = pd.DataFrame({'department': np.random.choice(['helium', 'neon', 'argon', 'krypton', 'xenon', 'radon', 'oganesson'],

1000, p=prob),

'left': np.random.choice(['yes', 'no'], 1000)})

with this code, I can see the value labels in my Anaconda's Jupyter however, they are not displayed in my Databricks notebook? any idea how to fix?

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
 
prob = np.random.rand(7) + 0.1
prob /= prob.sum()
df = pd.DataFrame({'department': np.random.choice(['helium', 'neon', 'argon', 'krypton', 'xenon', 'radon', 'oganesson'],
                                                  1000, p=prob),
                   'left': np.random.choice(['yes', 'no'], 1000)})
sns.set_style('white')
filter = df['left'] == 'yes'
g = sns.catplot(data=df[filter], kind='count', y='department', palette='mako_r',
            order=df[filter]['department'].value_counts(ascending=True).index)
for ax in g.axes.flat:
    ax.bar_label(ax.containers[0], fontsize=12)
    ax.margins(x=0.1)
plt.tight_layout()
plt.show()

the bar_label attributes are used in matplotlib.pyplot version 3.4.2.

I am using ML runtime 7.3. how can I upgrade?

thank you.