Update app.py

app.py

@@ -97,11 +97,11 @@ if not filtered_df.empty:
 
     # Iterate through the lines and extract the values
     for line in lines[:-1]:  # Skip the last two lines which might not contain forecast data
-        value = line.split()
+        period, value = line.split()
         num_float = float(value)
         monetary_value = f'R$ {num_float:,.2f}'  # Adding commas for thousands separator
         mes += 1
-        col1.write(f"{mes}: {monetary_value}")
+        col1.write(f"Mês {mes}: {monetary_value}")
 else:
     col1.warning('No data available for the selected filters.')
 
@@ -117,12 +117,15 @@ if not filtered_df.empty:
     # Split the string into lines
     lines = data_string.split('\n')
 
+    mes = 0
+
     # Iterate through the lines and extract the values
     for line in lines[:-1]:
         period, value = line.split()
         num_float = float(value)
         monetary_value = f'R$ {num_float:,.2f}'  # Adding commas for thousands separator
-        data.append({'Period': int(period), 'Monetary Value': num_float})
+        mes += 1
+        data.append({'Period': int(mes), 'Monetary Value': num_float})
 
     # Create a DataFrame from the list
     chart_data = pd.DataFrame(data)