Create app.py

app.py

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+import plotly.graph_objects as go
+import streamlit as st
+import pandas as pd
+from transformers import AutoModelWithLMHead
+
+# Create a list of the top five largest hospitals in the state of Minnesota
+hospitals_dict = [
+    {'name': 'Mayo Clinic',
+     'number_beds': 1569,
+     'latitude': 44.074,
+     'longitude': -92.4591},
+    {'name': 'United Hospital',
+     'number_beds': 663,
+     'latitude': 44.8794,
+     'longitude': -93.1748},
+    {'name': 'Allina Health',
+     'number_beds': 600,
+     'latitude': 44.9352,
+     'longitude': -93.0614},
+    {'name': 'Fairview Southdale Hospital',
+     'number_beds': 446,
+     'latitude': 44.8552,
+     'longitude': -93.3455},
+    {'name': 'St. Cloud Hospital',
+     'number_beds': 437,
+     'latitude': 45.5517,
+     'longitude': -94.1613}
+]
+
+# Create the dataframe from the list of dictionaries
+df = pd.DataFrame(hospitals_dict)
+
+# Create a treemap with plotly graph objects
+fig = go.Figure(data=go.Treemap(
+    labels=df['name'],
+    parents=['Minnesota'] * len(df),
+    values=df['number_beds'],
+))
+
+# Create the Huggingface model
+model = AutoModelWithLMHead.from_pretrained("distilbert-base-uncased")
+
+# Streamlit app
+st.title("Minnesota's Largest Hospitals")
+
+# Display the treemap
+st.plotly_chart(fig)
+
+# Display hospital information
+st.subheader("Hospital Information")
+st.write(df)
+
+# Save the dataframe as a CSV file
+st.subheader("Save CSV File")
+st.markdown("Click the button below to save the dataframe as a CSV file.")
+st.write(df.to_csv(index=False))