Tutorial

Install the package

python3 -m pip install -e .

To run the Streamlit dashboard, install the dashboard extras as well:

python3 -m pip install -e ".[dashboard]"

Load the cleaned data

from broadway_insights import load_clean_data

df = load_clean_data()
df.head()

Answer the research questions

from broadway_insights import (
    analyze_award_vs_theater_size,
    analyze_award_weekly_revenue,
    analyze_theater_size_vs_gross,
)

df = load_clean_data()

print(analyze_award_weekly_revenue(df))
print(analyze_theater_size_vs_gross(df))
print(analyze_award_vs_theater_size(df))

Build a chart in Python

from broadway_insights import build_revenue_scatter, load_clean_data

df = load_clean_data()
fig = build_revenue_scatter(df)
fig.show()

Run the Streamlit app

streamlit run streamlit_app.py

What to look for

• Check whether the Tony-flagged group shows a longer average tracked run.
• Use the scatterplot to inspect how theater capacity and revenue move together.
• Compare average theater size between Tony-flagged and non-flagged shows.