Update app.py

app.py

@@ -80,12 +80,16 @@ filtered_df = pd.concat(adjusted_rows)
 #col1, col2, col3 = st.columns(3) # This divides the page into three equal parts
 
 # Set custom width for columns
-col1_width = 400
-col2_width = 400
-col1, col2 = st.columns([col1_width, col2_width])
+col1_width = 260
+col2_width = 260
+col3_width = 260
+col1, col2, col3 = st.columns([col1_width, col2_width, col3_width])
 
 # Display the Forecasts values in the first column
-col1.header('Valores previstos')
+col1.header('Composição da RLIT')
+
+# Display the Forecasts values in the first column
+col2.header('Valores previstos')
 
 if not filtered_df.empty:
     data_string = filtered_df['Forecasts'].iloc[0]
@@ -101,12 +105,12 @@ if not filtered_df.empty:
         num_float = float(value)
         monetary_value = f'R$ {num_float:,.2f}'  # Adding commas for thousands separator
         mes += 1
-        col1.write(f"Mês {mes}: {monetary_value}")
+        col2.write(f"Mês {mes}: {monetary_value}")
 else:
-    col1.warning('No data available for the selected filters.')
+    col2.warning('No data available for the selected filters.')
 
 # Display the Forecasts values as line plots in the second column
-col2.header('Gráfico com previsões')
+col3.header('Gráfico com previsões')
 
 if not filtered_df.empty:
     data_string = filtered_df['Forecasts'].iloc[0]
@@ -134,15 +138,20 @@ if not filtered_df.empty:
     chart_data = chart_data.sort_values(by='Period')
 
     # Display line chart with "period" on X-axis and "Monetary Value" on Y-axis
-    col2.line_chart(chart_data.set_index('Period'))
+    col3.line_chart(chart_data.set_index('Period'))
 
 else:
-    col2.warning('No data available for the selected filters.')
+    col3.warning('No data available for the selected filters.')
 
 # Display the table in the third column
 #col3 = st.columns(1)  # You can use st.columns(1) to create a single column layout
 
-#col3.header('Resultados')
+col4_width = 400
+col5_width = 400
+col4, col5 = st.columns([col4_width, col5_width)
+
+col4.header('Realizado X Previsto')
+
 if not filtered_df.empty:
     # Filter the DataFrame for the selected institution
     tab_df = df[df['Instituição'] == selected_instituicao]
@@ -231,7 +240,7 @@ if not filtered_df.empty:
         st.error(f"Error in processing data: {str(e)}")
 
 else:
-    col3.warning('No data available for the selected filters.')
+    col5.warning('No data available for the selected filters.')
 
 
 st.markdown("""