Fix: Readme

streamlit_app.py

@@ -39,13 +39,23 @@ def get_cached_collections():
 @st.cache_data(ttl=300)  # Cache for 5 minutes
 def load_all_data(_collection):
     """Load and cache all data from MongoDB collection."""
-    data = list(_collection.find({}, {'_id': 0, 'Reported Date': 1, 'Modal Price (Rs./Quintal)': 1, 'Arrivals (Tonnes)': 1, 'State Name': 1, 'Market Name': 1}))
+    data = list(_collection.find({}))
     if not data:
         return pd.DataFrame()
     df = pd.DataFrame(data)
-    df['Reported Date'] = pd.to_datetime(df['Reported Date'])
-    df['Modal Price (Rs./Quintal)'] = pd.to_numeric(df['Modal Price (Rs./Quintal)'], errors='coerce')
-    df['Arrivals (Tonnes)'] = pd.to_numeric(df['Arrivals (Tonnes)'], errors='coerce')
+    
+    # Drop MongoDB _id field
+    if '_id' in df.columns:
+        df = df.drop(columns=['_id'])
+    
+    # Convert data types
+    if 'Reported Date' in df.columns:
+        df['Reported Date'] = pd.to_datetime(df['Reported Date'])
+    if 'Modal Price (Rs./Quintal)' in df.columns:
+        df['Modal Price (Rs./Quintal)'] = pd.to_numeric(df['Modal Price (Rs./Quintal)'], errors='coerce')
+    if 'Arrivals (Tonnes)' in df.columns:
+        df['Arrivals (Tonnes)'] = pd.to_numeric(df['Arrivals (Tonnes)'], errors='coerce')
+    
     return df
 
 
@@ -58,14 +68,24 @@ def get_filtered_data(_collection, state=None, market=None, days=30):
     if market:
         query_filter["Market Name"] = market
     
-    data = list(_collection.find(query_filter, {'_id': 0}))
+    data = list(_collection.find(query_filter))
     if not data:
         return pd.DataFrame()
     
     df = pd.DataFrame(data)
-    df['Reported Date'] = pd.to_datetime(df['Reported Date'])
-    df['Modal Price (Rs./Quintal)'] = pd.to_numeric(df['Modal Price (Rs./Quintal)'], errors='coerce')
-    df['Arrivals (Tonnes)'] = pd.to_numeric(df['Arrivals (Tonnes)'], errors='coerce')
+    
+    # Drop MongoDB _id field
+    if '_id' in df.columns:
+        df = df.drop(columns=['_id'])
+    
+    # Convert data types
+    if 'Reported Date' in df.columns:
+        df['Reported Date'] = pd.to_datetime(df['Reported Date'])
+    if 'Modal Price (Rs./Quintal)' in df.columns:
+        df['Modal Price (Rs./Quintal)'] = pd.to_numeric(df['Modal Price (Rs./Quintal)'], errors='coerce')
+    if 'Arrivals (Tonnes)' in df.columns:
+        df['Arrivals (Tonnes)'] = pd.to_numeric(df['Arrivals (Tonnes)'], errors='coerce')
+    
     return df