stopping erroneous dropping of NaN drawdown

app.py

@@ -152,7 +152,7 @@ def get_rolling_stats(df, lev, otimeheader, days):
         rolling_df = df[df[otimeheader] >= rollend]
 
         if len(rolling_df) > 0:
-            rolling_perc = rolling_df['Return Per Trade'].dropna().cumprod().values[-1]-1
+            rolling_perc = rolling_df['Return Per Trade'].drop('Drawdown %', axis=1).dropna().cumprod().values[-1]-1
         else: 
             rolling_perc = np.nan
     else:
@@ -583,7 +583,7 @@ def runapp() -> None:
                         df['Balance used in Trade'] = np.concatenate([[principal_balance], df['New Balance'].values[:-1]])
                     df['Net P/L Per Trade'] = (df['Return Per Trade']-1)*df['Balance used in Trade']
                     df['Cumulative P/L'] = df['Net P/L Per Trade'].cumsum()
-                    cum_pl = df.loc[df.dropna().index[-1],'Cumulative P/L'] + principal_balance
+                    cum_pl = df.loc[df.drop('Drawdown %', axis=1).dropna().index[-1],'Cumulative P/L'] + principal_balance
 
                     effective_return = 100*((cum_pl - principal_balance)/principal_balance)
 
@@ -595,7 +595,7 @@ def runapp() -> None:
                             f"{100*(cum_pl-principal_balance)/(principal_balance):.2f} %",
                         )
 
-                    st.line_chart(data=df.dropna(), x='Exit Date', y='Cumulative P/L', use_container_width=True)
+                    st.line_chart(data=df.drop('Drawdown %', axis=1).dropna(), x='Exit Date', y='Cumulative P/L', use_container_width=True)
 
                     df['Per Trade Return Rate'] = df['Return Per Trade']-1