How to plot shaded areas on a seaborn countplot - seaborn

Question

I would like to be able to show shaded areas on a seaborn countplot as shown below. The idea would be to show the covid lockown periods that cover the data period. I have the countplot, but i cant figure out how to add the the shaded area.
My current df contains dates of properties for sale (from domain.com.au), and i have a small dataset of covid dates:
The code that generates the seaborn plot:
fig, ax = plt.subplots(figsize=(16,10));
sns.countplot(data=df, x='dates', ax=ax)
representation of what i am looking to produce (created from excel).

Answer 1

Assuming your property dataset looks like this:
df = pd.DataFrame({
"date": ["2022-07-01", "2022-07-01", "2022-07-01", "2022-07-02", "2022-07-02", "2022-07-03", "2022-07-04", "2022-07-05", "2022-07-05", "2022-07-05", "2022-07-06"],
"prop": ['test'] * 11
})
df['date'] = pd.to_datetime(df['date']).dt.date
date prop
0 2022-07-01 test
1 2022-07-01 test
2 2022-07-01 test
3 2022-07-02 test
4 2022-07-02 test
5 2022-07-03 test
6 2022-07-04 test
7 2022-07-05 test
8 2022-07-05 test
9 2022-07-05 test
10 2022-07-06 test
Then you could do a bar plot of the counts and shade date ranges with matplotlib's axvspan:
fig, ax = plt.subplots(figsize=(16,10));
prop_count = df['date'].value_counts()
plt.bar(prop_count.index, prop_count.values)
for start_date, end_date in zip(covid_df['start_date'], covid_df['end_date']):
ax.axvspan(start_date, end_date, alpha=0.1, color='red')
plt.show()