Create analytics_tab.py

analytics_tab.py

@@ -0,0 +1,352 @@
+import gradio as gr
+import pandas as pd
+import plotly.graph_objects as go
+from datetime import datetime
+
+class AnalyticsTab:
+    def __init__(self, get_sheet_func):
+        """
+        Initialize the Analytics Tab
+        
+        Args:
+            get_sheet_func: Function to get Google Sheet
+        """
+        self.get_sheet = get_sheet_func
+    
+    def get_all_transactions(self):
+        """Get all transactions without interest calculations"""
+        try:
+            spreadsheet = self.get_sheet()
+            trans_sheet = spreadsheet.worksheet("Transactions")
+            data = trans_sheet.get_all_values()
+            
+            if len(data) <= 1:
+                return pd.DataFrame()
+            
+            df = pd.DataFrame(data[1:], columns=data[0])
+            df['Amount'] = pd.to_numeric(df['Amount'], errors='coerce')
+            df['Date'] = pd.to_datetime(df['Date'], errors='coerce')
+            df = df.sort_values('Date')
+            
+            # Calculate running balance without interest
+            df['Balance'] = df['Amount'].cumsum()
+            
+            return df
+        except Exception as e:
+            print(f"Error getting transactions: {str(e)}")
+            return pd.DataFrame()
+    
+    def get_transactions_display(self):
+        """Get transactions formatted for display"""
+        try:
+            df = self.get_all_transactions()
+            
+            if df.empty:
+                return None, "❌ No transactions found"
+            
+            # Format for display
+            display_df = df[['Date', 'Type', 'Bank Account', 'Amount', 'Balance']].copy()
+            display_df.columns = ['Date', 'Description', 'Bank Account', 'Amount (₹)', 'Balance (₹)']
+            display_df['Date'] = display_df['Date'].dt.strftime('%Y-%m-%d')
+            
+            return display_df, f"✅ Showing {len(display_df)} transactions"
+        except Exception as e:
+            return None, f"❌ Error loading transactions: {str(e)}"
+    
+    def get_bank_analytics(self, month=None, year=None):
+        """Get bank-wise analytics with optional month/year filter"""
+        try:
+            df = self.get_all_transactions()
+            
+            if df.empty:
+                return None, None, "❌ No transactions found"
+            
+            # Apply filters if provided
+            if month and year:
+                df = df[(df['Date'].dt.month == int(month)) & (df['Date'].dt.year == int(year))]
+            elif year:
+                df = df[df['Date'].dt.year == int(year)]
+            
+            if df.empty:
+                return None, None, "❌ No transactions found for the selected period"
+            
+            # Calculate bank-wise statistics
+            bank_stats = []
+            banks = df['Bank Account'].unique()
+            
+            for bank in banks:
+                bank_df = df[df['Bank Account'] == bank]
+                outgoing = abs(bank_df[bank_df['Amount'] < 0]['Amount'].sum())
+                incoming = bank_df[bank_df['Amount'] > 0]['Amount'].sum()
+                net = incoming - outgoing
+                
+                bank_stats.append({
+                    'Bank Account': bank,
+                    'Outgoing': outgoing,
+                    'Incoming': incoming,
+                    'Net': net
+                })
+            
+            stats_df = pd.DataFrame(bank_stats)
+            
+            # Create horizontal bar chart
+            fig = go.Figure()
+            
+            fig.add_trace(go.Bar(
+                name='Outgoing',
+                y=stats_df['Bank Account'],
+                x=stats_df['Outgoing'],
+                orientation='h',
+                marker_color='#e74c3c',
+                text=stats_df['Outgoing'].apply(lambda x: f'₹{x:,.2f}'),
+                textposition='auto'
+            ))
+            
+            fig.add_trace(go.Bar(
+                name='Incoming',
+                y=stats_df['Bank Account'],
+                x=stats_df['Incoming'],
+                orientation='h',
+                marker_color='#27ae60',
+                text=stats_df['Incoming'].apply(lambda x: f'₹{x:,.2f}'),
+                textposition='auto'
+            ))
+            
+            filter_text = ""
+            if month and year:
+                filter_text = f" ({datetime(int(year), int(month), 1).strftime('%B %Y')})"
+            elif year:
+                filter_text = f" ({year})"
+            
+            fig.update_layout(
+                title=f"Bank-wise Transaction Analytics{filter_text}",
+                xaxis_title="Amount (₹)",
+                yaxis_title="Bank Account",
+                barmode='group',
+                height=400,
+                font=dict(size=12),
+                showlegend=True
+            )
+            
+            # Create summary HTML
+            summary_html = f"""
+            <div style="background: linear-gradient(135deg, #3498db 0%, #2c3e50 100%); padding: 30px; border-radius: 15px; margin: 20px 0;">
+                <h2 style="color: white; text-align: center; margin-bottom: 25px;">📊 Bank-wise Analytics{filter_text}</h2>
+            """
+            
+            for _, row in stats_df.iterrows():
+                summary_html += f"""
+                <div style="background-color: rgba(255,255,255,0.95); border-radius: 10px; padding: 20px; margin-bottom: 15px;">
+                    <h3 style="color: #2c3e50; margin-bottom: 15px;">🏦 {row['Bank Account']}</h3>
+                    <table style="width: 100%; border-collapse: collapse;">
+                        <tr>
+                            <td style="padding: 10px; font-size: 16px; color: #e74c3c; font-weight: bold;">Outgoing:</td>
+                            <td style="padding: 10px; font-size: 18px; text-align: right; color: #e74c3c; font-weight: bold;">₹{row['Outgoing']:,.2f}</td>
+                        </tr>
+                        <tr>
+                            <td style="padding: 10px; font-size: 16px; color: #27ae60; font-weight: bold;">Incoming:</td>
+                            <td style="padding: 10px; font-size: 18px; text-align: right; color: #27ae60; font-weight: bold;">₹{row['Incoming']:,.2f}</td>
+                        </tr>
+                        <tr style="border-top: 2px solid #34495e;">
+                            <td style="padding: 10px; font-size: 16px; color: #34495e; font-weight: bold;">Net:</td>
+                            <td style="padding: 10px; font-size: 18px; text-align: right; color: {'#27ae60' if row['Net'] >= 0 else '#e74c3c'}; font-weight: bold;">₹{abs(row['Net']):,.2f} {'(Surplus)' if row['Net'] >= 0 else '(Deficit)'}</td>
+                        </tr>
+                    </table>
+                </div>
+                """
+            
+            summary_html += "</div>"
+            
+            return fig, summary_html, "✅ Analytics generated successfully"
+        
+        except Exception as e:
+            return None, None, f"❌ Error generating analytics: {str(e)}"
+    
+    def get_daily_transactions(self, selected_date):
+        """Get day-wise transaction details"""
+        try:
+            if not selected_date:
+                return None, "❌ Please select a date"
+            
+            df = self.get_all_transactions()
+            
+            if df.empty:
+                return None, "❌ No transactions found"
+            
+            # Convert selected date to datetime
+            selected_dt = pd.to_datetime(selected_date)
+            
+            # Filter for selected date
+            daily_df = df[df['Date'].dt.date == selected_dt.date()]
+            
+            if daily_df.empty:
+                return None, f"❌ No transactions found for {selected_date}"
+            
+            # Create summary table
+            outgoing_total = abs(daily_df[daily_df['Amount'] < 0]['Amount'].sum())
+            incoming_total = daily_df[daily_df['Amount'] > 0]['Amount'].sum()
+            
+            # Get outgoing details
+            outgoing_details = []
+            outgoing_df = daily_df[daily_df['Amount'] < 0]
+            for _, row in outgoing_df.iterrows():
+                outgoing_details.append({
+                    'Farmer': row['Farmer Name'],
+                    'Bank Account': row['Bank Account'],
+                    'Amount': abs(row['Amount'])
+                })
+            
+            # Get incoming details
+            incoming_details = []
+            incoming_df = daily_df[daily_df['Amount'] > 0]
+            for _, row in incoming_df.iterrows():
+                incoming_details.append({
+                    'Farmer': row['Farmer Name'],
+                    'Bank Account': row['Bank Account'],
+                    'Amount': row['Amount']
+                })
+            
+            # Create HTML summary
+            summary_html = f"""
+            <div style="background: linear-gradient(135deg, #ff6b6b 0%, #feca57 100%); padding: 30px; border-radius: 15px; margin: 20px 0;">
+                <h2 style="color: white; text-align: center; margin-bottom: 25px;">📅 Daily Transaction Summary: {selected_date}</h2>
+                
+                <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 20px; margin-bottom: 20px;">
+                    <div style="background-color: rgba(255,255,255,0.95); border-radius: 10px; padding: 20px;">
+                        <h3 style="color: #e74c3c; text-align: center; margin-bottom: 15px;">💸 Outgoing</h3>
+                        <p style="font-size: 28px; font-weight: bold; text-align: center; color: #e74c3c; margin: 0;">₹{outgoing_total:,.2f}</p>
+                        <p style="text-align: center; color: #666; margin-top: 5px;">{len(outgoing_details)} transaction(s)</p>
+                    </div>
+                    
+                    <div style="background-color: rgba(255,255,255,0.95); border-radius: 10px; padding: 20px;">
+                        <h3 style="color: #27ae60; text-align: center; margin-bottom: 15px;">💰 Incoming</h3>
+                        <p style="font-size: 28px; font-weight: bold; text-align: center; color: #27ae60; margin: 0;">₹{incoming_total:,.2f}</p>
+                        <p style="text-align: center; color: #666; margin-top: 5px;">{len(incoming_details)} transaction(s)</p>
+                    </div>
+                </div>
+            """
+            
+            # Add outgoing details
+            if outgoing_details:
+                summary_html += """
+                <div style="background-color: rgba(255,255,255,0.95); border-radius: 10px; padding: 20px; margin-bottom: 15px;">
+                    <h3 style="color: #e74c3c; margin-bottom: 15px;">📤 Outgoing Transactions:</h3>
+                    <table style="width: 100%; border-collapse: collapse;">
+                        <tr style="background-color: #f8f9fa; font-weight: bold;">
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6;">Farmer</td>
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6;">Bank Account</td>
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6; text-align: right;">Amount</td>
+                        </tr>
+                """
+                for detail in outgoing_details:
+                    summary_html += f"""
+                        <tr>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6;">{detail['Farmer']}</td>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6;">{detail['Bank Account']}</td>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6; text-align: right; color: #e74c3c; font-weight: bold;">₹{detail['Amount']:,.2f}</td>
+                        </tr>
+                    """
+                summary_html += "</table></div>"
+            
+            # Add incoming details
+            if incoming_details:
+                summary_html += """
+                <div style="background-color: rgba(255,255,255,0.95); border-radius: 10px; padding: 20px;">
+                    <h3 style="color: #27ae60; margin-bottom: 15px;">📥 Incoming Transactions:</h3>
+                    <table style="width: 100%; border-collapse: collapse;">
+                        <tr style="background-color: #f8f9fa; font-weight: bold;">
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6;">Farmer</td>
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6;">Bank Account</td>
+                            <td style="padding: 10px; border-bottom: 2px solid #dee2e6; text-align: right;">Amount</td>
+                        </tr>
+                """
+                for detail in incoming_details:
+                    summary_html += f"""
+                        <tr>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6;">{detail['Farmer']}</td>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6;">{detail['Bank Account']}</td>
+                            <td style="padding: 10px; border-bottom: 1px solid #dee2e6; text-align: right; color: #27ae60; font-weight: bold;">₹{detail['Amount']:,.2f}</td>
+                        </tr>
+                    """
+                summary_html += "</table></div>"
+            
+            summary_html += "</div>"
+            
+            return summary_html, f"✅ Found {len(daily_df)} transaction(s) for {selected_date}"
+        
+        except Exception as e:
+            return None, f"❌ Error getting daily transactions: {str(e)}"
+    
+    def create_tab(self):
+        """Create the Analytics tab interface"""
+        with gr.Tab("📈 Analytics & Insights"):
+            gr.Markdown("## Transaction Analytics Dashboard")
+            gr.Markdown("View all transactions and analyze bank-wise performance")
+            
+            # Section 1: All Transactions
+            with gr.Accordion("📋 All Transactions (Without Interest)", open=True):
+                load_trans_btn = gr.Button("Load All Transactions", variant="primary", size="lg")
+                trans_status = gr.Textbox(label="Status", interactive=False)
+                all_trans_df = gr.Dataframe(
+                    label="All Transactions",
+                    interactive=False,
+                    wrap=True
+                )
+            
+            gr.Markdown("---")
+            
+            # Section 2: Bank-wise Analytics
+            with gr.Accordion("🏦 Bank-wise Analytics", open=True):
+                gr.Markdown("### Filter Transactions")
+                with gr.Row():
+                    month_filter = gr.Dropdown(
+                        label="Month (Optional)",
+                        choices=[""] + [str(i) for i in range(1, 13)],
+                        value="",
+                        allow_custom_value=False
+                    )
+                    year_filter = gr.Dropdown(
+                        label="Year (Optional)",
+                        choices=[""] + [str(year) for year in range(2020, 2031)],
+                        value="",
+                        allow_custom_value=False
+                    )
+                
+                generate_analytics_btn = gr.Button("Generate Analytics", variant="primary", size="lg")
+                
+                analytics_status = gr.Textbox(label="Status", interactive=False)
+                analytics_summary = gr.HTML()
+                analytics_chart = gr.Plot(label="Bank-wise Transaction Comparison")
+            
+            gr.Markdown("---")
+            
+            # Section 3: Daily Transaction Details
+            with gr.Accordion("📅 Daily Transaction Details", open=True):
+                gr.Markdown("### Select a Date to View Daily Transactions")
+                daily_date = gr.Textbox(
+                    label="Date (YYYY-MM-DD)",
+                    placeholder="2024-01-15"
+                )
+                get_daily_btn = gr.Button("Get Daily Details", variant="primary", size="lg")
+                
+                daily_status = gr.Textbox(label="Status", interactive=False)
+                daily_summary = gr.HTML()
+            
+            # Event handlers
+            load_trans_btn.click(
+                fn=self.get_transactions_display,
+                inputs=[],
+                outputs=[all_trans_df, trans_status]
+            )
+            
+            generate_analytics_btn.click(
+                fn=lambda m, y: self.get_bank_analytics(m if m else None, y if y else None),
+                inputs=[month_filter, year_filter],
+                outputs=[analytics_chart, analytics_summary, analytics_status]
+            )
+            
+            get_daily_btn.click(
+                fn=self.get_daily_transactions,
+                inputs=[daily_date],
+                outputs=[daily_summary, daily_status]
+            )