Update app.py

app.py

@@ -3,12 +3,13 @@ import pandas as pd
 import matplotlib.pyplot as plt
 
 def process_data(df):
-    # Clean data and consolidate categories
+    # Clean data and handle missing values
     df = df[['Project Category', 'Logged']].copy()
+    df = df.dropna(subset=['Project Category'])  # Remove rows with missing categories
     
-    # Map to main categories
+    # Convert to string and consolidate categories
     df['Category'] = df['Project Category'].apply(
-        lambda x: 'Billable' if 'Billable' in x else x.strip()
+        lambda x: 'Billable' if 'Billable' in str(x) else str(x).strip()
     )
     
     # Aggregate data
@@ -31,9 +32,13 @@ def create_pie_chart(data):
     ax.set_title('Overall Utilization', pad=20)
     return fig
 
-def create_bar_chart(data):
+def create_bar_chart(df):
+    # Filter and prepare non-billable data
+    non_billable = df[df['Category'] == 'Non-Billable']
+    non_billable = non_billable.groupby('Project Category')['Logged'].sum().reset_index()
+    
     fig, ax = plt.subplots(figsize=(10, 4))
-    data[data['Category'] == 'Non-Billable'].plot(
+    non_billable.plot(
         kind='bar',
         x='Project Category',
         y='Logged',
@@ -51,29 +56,36 @@ def main():
     uploaded_file = st.file_uploader("Upload Timesheet", type=['xls', 'xlsx'])
     
     if uploaded_file:
-        df = pd.read_excel(uploaded_file, sheet_name='Report')
-        processed_data = process_data(df)
-        
-        # Show main visualization
-        st.header("Overall Utilization")
-        col1, col2 = st.columns([2, 1])
-        
-        with col1:
-            st.pyplot(create_pie_chart(processed_data))
+        try:
+            df = pd.read_excel(uploaded_file, sheet_name='Report')
+            processed_data = process_data(df)
+            
+            # Show main visualization
+            st.header("Overall Utilization")
+            col1, col2 = st.columns([2, 1])
+            
+            with col1:
+                if not processed_data.empty:
+                    st.pyplot(create_pie_chart(processed_data))
+                else:
+                    st.warning("No data available for visualization")
+            
+            with col2:
+                st.dataframe(
+                    processed_data[['Category', 'Logged', 'Percentage']],
+                    hide_index=True,
+                    column_config={
+                        'Logged': 'Hours',
+                        'Percentage': st.column_config.NumberColumn(format="%.1f%%")
+                    }
+                )
+            
+            # Show non-billable details
+            st.header("Non-Billable Breakdown")
+            st.pyplot(create_bar_chart(processed_data))
             
-        with col2:
-            st.dataframe(
-                processed_data[['Category', 'Logged', 'Percentage']],
-                hide_index=True,
-                column_config={
-                    'Logged': 'Hours',
-                    'Percentage': st.column_config.NumberColumn(format="%.1f%%")
-                }
-            )
-        
-        # Show non-billable details
-        st.header("Non-Billable Breakdown")
-        st.pyplot(create_bar_chart(df))
+        except Exception as e:
+            st.error(f"Error processing file: {str(e)}")
 
 if __name__ == "__main__":
     main()