minor changes

app.py

@@ -1,16 +1,11 @@
 import locale
+
 import gradio as gr
-import matplotlib.pyplot as plt
-import numpy as np
-import numpy_financial as npf
 import pandas as pd
-import plotly.graph_objects as go
-import seaborn as sns
-from pandas.tseries.offsets import DateOffset, MonthEnd
-from scipy import optimize
+from pandas.tseries.offsets import DateOffset
 
 from portfolio import calculate_portfolio_returns
-from utils import get_all_mf_schemes_df,get_mf_scheme_data
+from utils import get_all_mf_schemes_df, get_mf_scheme_data
 
 js_func = """
 function refresh() {

indicators.py

@@ -20,10 +20,8 @@ def get_investment_sharpe_ratio(investment_df, start_date, end_date, SIP_date,ri
     # calculate annualized standard deviation of monthly returns
     annualized_sd = return_df['monthly_return'].std()*np.sqrt(12)
     monthly_mean_return = return_df['monthly_return'].mean()
-    print(monthly_mean_return)
+    # calculate annualized return, as the risk free rate is annualized
     annualized_return = ((1+monthly_mean_return/100)**12 - 1)*100
-    print(annualized_return)
-
     # calculate Sharpe Ratio
     return ((annualized_return - risk_free_rate) / annualized_sd)