sss

app.py

@@ -53,8 +53,10 @@ def valuation_predictor(goals, assists, y_cards, r_cards,
 
 df = fg.read()
 df = df.drop(columns=["player_id", "date"])
-df_present = pd.DataFrame(columns=["Player name", "League", "Goals", "Assists", "Yellow cards", "Red cards", "Minutes played", "Height (cm)", "Age", "Months left on contract", "Team made goals", "Team conceded goals", "Team clean sheets", "Actual market value (EUR)", "Model predicted market value (EUR)"])
 
+
+
+new_rows = []
 for index, row in df.iterrows():
     league = ""
     if row['league_es1']:
@@ -87,9 +89,11 @@ for index, row in df.iterrows():
     }
 
     # Append new row to df_present
-    df_present = df_present.append(new_row, ignore_index=True)
+    new_rows.append(new_row)
+    
+    #predicted_value = valuation_predictor()
     
-    predicted_value = valuation_predictor()
+df_present = pd.DataFrame(new_rows, columns=["Player name", "League", "Goals", "Assists", "Yellow cards", "Red cards", "Minutes played", "Height (cm)", "Age", "Months left on contract", "Team made goals", "Team conceded goals", "Team clean sheets", "Actual market value (EUR)", "Model predicted market value (EUR)"])
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     with gr.Row():