Update app.py

app.py

@@ -1,73 +1,72 @@
 import streamlit as st
+import pandas as pd
+import folium
+from streamlit_folium import st_folium
 
-# Function to parse the data for a specific state using its two-letter code
-def parse_state_data(data, state_code):
-    state_data = {}
-    current_category = None
+# Data for each state
+data = {
+    "MA": {
+        "Companies": [
+            {"Name": "Amazon (MA)", "Employees": 7000, "City": "Boston"},
+            {"Name": "MIT (Cambridge, MA)", "Employees": 6300, "City": "Cambridge"},
+            {"Name": "Fidelity Investments (Boston, MA)", "Employees": 5000, "City": "Boston"},
+            {"Name": "State Street Corporation (Boston, MA)", "Employees": 4000, "City": "Boston"},
+            {"Name": "Partners Healthcare System (Boston, MA)", "Employees": 3500, "City": "Boston"}
+        ],
+        "Cities": [
+            {"Name": "Boston", "Population": 700000, "Income": 75000, "Latitude": 42.3601, "Longitude": -71.0589},
+            {"Name": "Cambridge", "Population": 120000, "Income": 85000, "Latitude": 42.3736, "Longitude": -71.1097},
+            # Add other cities...
+        ],
+        "Hospitals": [
+            {"Name": "Massachusetts General Hospital", "Beds": 1000, "City": "Boston"},
+            # Add other hospitals...
+        ]
+    },
+    # Add data for CA and WA...
+}
 
-    for line in data:
-        line = line.strip()
-        if line.startswith(state_code + ":"):
-            state_data["Name"] = line[len(state_code) + 1:]
-        elif line.startswith("# Large Companies"):
-            current_category = "Large Companies"
-            state_data[current_category] = []
-        elif line.startswith("# Cities"):
-            current_category = "Cities"
-            state_data[current_category] = []
-        elif line.startswith("# Hospitals"):
-            current_category = "Hospitals"
-            state_data[current_category] = []
-        elif line.startswith("#"):
-            current_category = None
-        elif current_category:
-            state_data[current_category].append(line)
+# Streamlit page configuration
+st.set_page_config(page_title="State Data", layout="wide")
 
-    return state_data
+# Main title
+st.title("State Information Dashboard")
 
-# Function to create a search URL for Wikipedia:
-def create_search_url_wikipedia(query):
-    base_url = "https://www.wikipedia.org/search-redirect.php?family=wikipedia&language=en&search="
-    return base_url + query.replace(' ', '+').replace('–', '%E2%80%93').replace('&', 'and')
+# Select a state
+selected_state = st.selectbox("Select a State:", ["MA", "CA", "WA"])
 
-# Function to create a search URL for YouTube:
-def create_search_url_youtube(query):
-    base_url = "https://www.youtube.com/results?search_query="
-    return base_url + query.replace(' ', '+').replace('–', '%E2%80%93').replace('&', 'and')
+# Process selected state data
+companies_df = pd.DataFrame(data[selected_state]["Companies"])
+cities_df = pd.DataFrame(data[selected_state]["Cities"])
+hospitals_df = pd.DataFrame(data[selected_state]["Hospitals"])
 
-# Read and parse the data from the text file
-with open("states_data.txt", "r") as file:
-    data = file.readlines()
+# Display DataFrames
+st.write("Companies:")
+st.dataframe(companies_df)
+st.write("Cities:")
+st.dataframe(cities_df)
+st.write("Hospitals:")
+st.dataframe(hospitals_df)
 
-# Streamlit page configuration
-st.set_page_config(page_title="State Data", layout="wide")
-
-# Main title
-st.title("Top Five Lists for Different States 🏙️")
+# Create a Folium map for the selected state
+m = folium.Map(location=[cities_df["Latitude"].mean(), cities_df["Longitude"].mean()], zoom_start=7)
 
-# Select a state using a two-letter code
-selected_state = st.selectbox("Select a State:", ["MA: Massachusetts", "CA: California", "WA: Washington"])
+# Add markers for cities, companies, and hospitals
+for _, city in cities_df.iterrows():
+    folium.Marker([city["Latitude"], city["Longitude"]], tooltip=f"{city['Name']}").add_to(m)
 
-# Parse the data for the selected state
-state_code = selected_state.split(":")[0]
-state_data = parse_state_data(data, state_code)
+for _, company in companies_df.iterrows():
+    # Find the city's coordinates
+    city = cities_df[cities_df["Name"] == company["City"]].iloc[0]
+    folium.Marker([city["Latitude"], city["Longitude"]], tooltip=f"{company['Name']}").add_to(m)
 
-# Display the state name
-st.header(f"{state_data['Name']} 🏆")
+for _, hospital in hospitals_df.iterrows():
+    # Find the city's coordinates
+    city = cities_df[cities_df["Name"] == hospital["City"]].iloc[0]
+    folium.Marker([city["Latitude"], city["Longitude"]], tooltip=f"{hospital['Name']}").add_to(m)
 
-# Display the top five lists
-for category, nominees in state_data.items():
-    if category != "Name":
-        st.subheader(f"{category}")
-        with st.expander(f"View {category} Nominees"):
-            for nominee in nominees[:5]:  # Show only the top five
-                col1, col2, col3 = st.columns([4, 1, 1])
-                with col1:
-                    st.markdown(f"* {nominee}")
-                with col2:
-                    st.markdown(f"[Wikipedia]({create_search_url_wikipedia(nominee)})")
-                with col3:
-                    st.markdown(f"[YouTube]({create_search_url_youtube(nominee)})")
+# Display the map
+st_folium(m, width=700, height=500)
 
 # Footer
-st.caption("Source: Wikipedia and YouTube")
+st.caption("Data source: User provided")