Update app.py

app.py

@@ -4,63 +4,89 @@ import gradio as gr
 import os
 
 # Constants
-API_URL = 'https://api.electricitymap.org/v3/power-breakdown/latest'
+API_URL = 'https://api.electricitymap.org/v3/carbon-intensity/latest'
 API_TOKEN = os.getenv('ELECTRICITYMAP_API_TOKEN')
 
-# Define the data for company headquarters
+# Define the data for NIFTY 50 company headquarters
 data = {
-    "Company": ["Apple", "Microsoft", "NVIDIA", "Alphabet (Google)", "Amazon", "Saudi Aramco", 
-                "Meta Platforms (Facebook)", "TSMC", "Berkshire Hathaway", "Eli Lilly", 
-                "Tesla", "Broadcom", "Novo Nordisk", "JPMorgan Chase", "Walmart"],
-    "Location": ["Cupertino, California, USA", "Redmond, Washington, USA", "Santa Clara, California, USA", 
-                 "Mountain View, California, USA", "Seattle, Washington, USA", "Dhahran, Eastern Province, Saudi Arabia", 
-                 "Menlo Park, California, USA", "Hsinchu, Taiwan", "Omaha, Nebraska, USA", "Indianapolis, Indiana, USA", 
-                 "Palo Alto, California, USA", "San Jose, California, USA", "Bagsværd, Denmark", 
-                 "New York City, New York, USA", "Bentonville, Arkansas, USA"],
-    "Latitude": [37.3349, 47.6424, 37.3706, 37.4219, 47.6062, 26.3032, 
-                 37.4848, 24.7851, 41.2565, 39.7684, 37.3947, 37.3382, 
-                 55.7500, 40.7128, 36.3729],
-    "Longitude": [-122.0090, -122.1362, -121.9669, -122.0840, -122.3321, 50.1503, 
-                  -122.1484, 121.0177, -95.9345, -86.1581, -122.1503, -121.8863, 
-                  12.4500, -74.0060, -94.2088]
+    "Company": ["Reliance Industries", "Tata Consultancy Services", "HDFC Bank", "Infosys", "Hindustan Unilever", 
+                "ICICI Bank", "Kotak Mahindra Bank", "SBI", "Bharti Airtel", "HCL Technologies",
+                "Asian Paints", "Bajaj Finance", "ITC", "Adani Green Energy", "Axis Bank",
+                "Maruti Suzuki", "Larsen & Toubro", "Tata Motors", "Sun Pharma", "HDFC",
+                "Wipro", "UltraTech Cement", "Nestle India", "Adani Ports", "Bajaj Finserv",
+                "Titan Company", "Grasim Industries", "Mahindra & Mahindra", "Tech Mahindra", "Divi's Laboratories",
+                "JSW Steel", "Power Grid Corporation", "Tata Steel", "Britannia Industries", "Hindalco Industries",
+                "Eicher Motors", "Dr. Reddy's Laboratories", "Tata Consumer Products", "HDFC Life", "SBI Life Insurance",
+                "Hero MotoCorp", "Coal India", "Indian Oil Corporation", "Oil and Natural Gas Corporation", "Bharat Petroleum",
+                "Cipla", "Shree Cement", "Bajaj Auto", "IndusInd Bank", "NTPC"],
+    "Location": ["Mumbai, Maharashtra", "Mumbai, Maharashtra", "Mumbai, Maharashtra", "Bengaluru, Karnataka", "Mumbai, Maharashtra",
+                 "Mumbai, Maharashtra", "Mumbai, Maharashtra", "Mumbai, Maharashtra", "New Delhi, Delhi", "Noida, Uttar Pradesh",
+                 "Mumbai, Maharashtra", "Pune, Maharashtra", "Kolkata, West Bengal", "Ahmedabad, Gujarat", "Mumbai, Maharashtra",
+                 "New Delhi, Delhi", "Mumbai, Maharashtra", "Mumbai, Maharashtra", "Mumbai, Maharashtra", "Mumbai, Maharashtra",
+                 "Bengaluru, Karnataka", "Mumbai, Maharashtra", "Gurugram, Haryana", "Ahmedabad, Gujarat", "Pune, Maharashtra",
+                 "Bengaluru, Karnataka", "Nagda, Madhya Pradesh", "Mumbai, Maharashtra", "Pune, Maharashtra", "Hyderabad, Telangana",
+                 "Mumbai, Maharashtra", "New Delhi, Delhi", "Mumbai, Maharashtra", "Bengaluru, Karnataka", "Mumbai, Maharashtra",
+                 "Gurugram, Haryana", "Hyderabad, Telangana", "Mumbai, Maharashtra", "Mumbai, Maharashtra", "Mumbai, Maharashtra",
+                 "New Delhi, Delhi", "Kolkata, West Bengal", "New Delhi, Delhi", "New Delhi, Delhi", "Mumbai, Maharashtra",
+                 "Mumbai, Maharashtra", "Kolkata, West Bengal", "Pune, Maharashtra", "Mumbai, Maharashtra", "New Delhi, Delhi"],
+    "Latitude": [19.0760, 19.0760, 19.0760, 12.9716, 19.0760,
+                 19.0760, 19.0760, 19.0760, 28.6139, 28.5355,
+                 19.0760, 18.5204, 22.5726, 23.0225, 19.0760,
+                 28.6139, 19.0760, 19.0760, 19.0760, 19.0760,
+                 12.9716, 19.0760, 28.4595, 23.0225, 18.5204,
+                 12.9716, 23.5330, 19.0760, 18.5204, 17.3850,
+                 19.0760, 28.6139, 19.0760, 12.9716, 19.0760,
+                 28.4595, 17.3850, 19.0760, 19.0760, 19.0760,
+                 28.6139, 22.5726, 28.6139, 28.6139, 19.0760,
+                 19.0760, 22.5726, 18.5204, 19.0760, 28.6139],
+    "Longitude": [72.8777, 72.8777, 72.8777, 77.5946, 72.8777,
+                  72.8777, 72.8777, 72.8777, 77.2090, 77.3910,
+                  72.8777, 73.8567, 88.3639, 72.5714, 72.8777,
+                  77.2090, 72.8777, 72.8777, 72.8777, 72.8777,
+                  77.5946, 72.8777, 77.0266, 72.5714, 73.8567,
+                  77.5946, 75.4254, 72.8777, 73.8567, 78.4867,
+                  72.8777, 77.2090, 72.8777, 77.5946, 72.8777,
+                  77.0266, 78.4867, 72.8777, 72.8777, 72.8777,
+                  77.2090, 88.3639, 77.2090, 77.2090, 72.8777,
+                  72.8777, 88.3639, 73.8567, 72.8777, 77.2090]
 }
 
 df = pd.DataFrame(data)
 
 # Function to make API request
-def get_power_breakdown(lat, lon):
+def get_carbon_intensity(lat, lon):
     headers = {'auth-token': API_TOKEN}
     params = {'lat': lat, 'lon': lon}
     response = requests.get(API_URL, headers=headers, params=params)
     if response.status_code == 200:
-        return response.json().get('fossilFreePercentage', 'N/A')
+        return response.json().get('carbonIntensity', 'N/A')
     else:
         return 'Error'
 
-# Define the function to fetch fossil-free percentage for all companies
-def fetch_fossil_free_percentages():
+# Define the function to fetch carbon intensity for all companies
+def fetch_carbon_intensities():
     results = []
     for index, row in df.iterrows():
         lat, lon = row["Latitude"], row["Longitude"]
-        fossil_free_percentage = get_power_breakdown(lat, lon)
+        carbon_intensity = get_carbon_intensity(lat, lon)
         results.append({
             "Company": row["Company"],
             "Location": row["Location"],
             "Latitude": row["Latitude"],
             "Longitude": row["Longitude"],
-            "Fossil-Free Percentage": fossil_free_percentage
+            "Carbon Intensity": carbon_intensity
         })
     return pd.DataFrame(results)
 
 # Define Gradio interface
-def show_fossil_free_table():
-    result_df = fetch_fossil_free_percentages()
+def show_carbon_intensity_table():
+    result_df = fetch_carbon_intensities()
     return result_df
 
-gr_interface = gr.Interface(fn=show_fossil_free_table, 
+gr_interface = gr.Interface(fn=show_carbon_intensity_table, 
                             inputs=None, 
                             outputs="dataframe", 
-                            title="Fossil-Free Percentage by Company Headquarters",
-                            description="Click the button below to see the latest fossil-free energy usage percentages for the top market cap company headquarters.")
+                            title="Carbon Intensity by NIFTY 50 Company Headquarters",
+                            description="Click the button below to see the latest carbon intensity for NIFTY 50 company headquarters.")
 
 gr_interface.launch()