Update app.py

app.py

@@ -1,66 +1,56 @@
 import streamlit as st
+import pandas as pd
 from apify_client import ApifyClient
 import requests
-import pandas as pd
 
+# Function to fetch Google Maps info
 def fetch_google_maps_info(website_name):
     apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
-
-    # Prepare the Actor input for Google Maps
-    run_input = {
-        "searchStringsArray": [website_name],
-        # ... other parameters
-    }
-
-    # Run the Actor and wait for it to finish
+    run_input = {"searchStringsArray": [website_name]}
     run = apify_client.actor("nwua9Gu5YrADL7ZDj").call(run_input=run_input)
-
-    # Fetch Actor results from the run's dataset
     items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
     return items[0] if items else None
 
+# Function to fetch weather info
 def fetch_weather_info(lat, lon):
     API_KEY = "91b23cab82ee530b2052c8757e343b0d"
     url = f"https://api.openweathermap.org/data/3.0/onecall?lat={lat}&lon={lon}&exclude=hourly,daily&appid={API_KEY}"
     response = requests.get(url)
     return response.json()
 
-# Main Streamlit app
+# Streamlit app
+st.title("Data Visualization")
+
 website_name = st.text_input("Enter a website / company name:")
 
 if website_name:
     google_maps_data = fetch_google_maps_info(website_name)
 
     if google_maps_data:
-        # Formatting and displaying all the data in Streamlit table
-        table_data = {}
-        for key, value in google_maps_data.items():
-            # Handle lists of strings
-            if isinstance(value, list) and all(isinstance(item, str) for item in value):
-                table_data[key] = ", ".join(value)
-            # Handle lists of dictionaries
-            elif isinstance(value, list) and all(isinstance(item, dict) for item in value):
-                table_data[key] = ", ".join([str(item) for item in value])
-            # Handle nested dictionaries
-            elif isinstance(value, dict):
-                table_data[key] = ", ".join([f"{k}: {v}" for k, v in value.items()])
-            else:
-                table_data[key] = value
-
-        st.table(table_data)
-
-        # Fetch weather info based on Google Maps data's location
+        # Display location and fetch weather info
         lat = google_maps_data["location"]["lat"]
         lng = google_maps_data["location"]["lng"]
-
         if lat and lng:
-            # Display location on Streamlit map
-            df_location = pd.DataFrame({'lat': [lat], 'lon': [lng]})
-            st.map(df_location)
-
             weather_data = fetch_weather_info(lat, lng)
             current_weather = weather_data.get("current", {})
-            st.write(f"Temperature: {current_weather.get('temp')}°C")
-            st.write(f"Weather: {current_weather.get('weather')[0].get('description')}")
+            st.write(f"**Location:** {lat}, {lng}")
+            st.write(f"**Temperature:** {current_weather.get('temp')}°C")
+            st.write(f"**Weather:** {current_weather.get('weather')[0].get('description')}")
+
+        # Display occupancy chart
+        st.subheader("Occupancy Data")
+        df_occupancy = pd.DataFrame()
+        for day, day_data in occupancy_data.items():
+            if day_data:
+                hours = [entry['hour'] for entry in day_data]
+                occupancy = [entry['occupancyPercent'] for entry in day_data]
+                df_occupancy[day] = pd.Series(occupancy, index=hours)
+        st.line_chart(df_occupancy, use_container_width=True)
+
+        # Display reviews data
+        st.subheader("Reviews Data")
+        st.write(f"Total Reviews Count: {reviews_data['reviewsCount']}")
+        df_reviews = pd.DataFrame(list(reviews_data['reviewsDistribution'].items()), columns=['Review', 'Count'])
+        st.bar_chart(df_reviews.set_index('Review'))
     else:
         st.write("No results found for this website / company name on Google Maps.")