add growth metrics

pages/1_Fundamentals.py

@@ -129,7 +129,6 @@ with st.form(key="selecting columns"):
     submit_button = st.form_submit_button(label='Compute Metrics')
 
     if submit_button and symbols and strategy_selection == 'Value':
-        beta_dfs = []
         gains_data = {}
         hash_map = {}
         
@@ -174,4 +173,39 @@ with st.form(key="selecting columns"):
         st.write(df_final)
 
     if submit_button and symbols and strategy_selection == 'Growth':
-       st.write("Not built yet...")
+
+      hash_map,gains_data = {},{}
+      for ticker in symbols:
+          # make all the API calls and capture return json
+          basic_info = get_industry(ticker) 
+          metric_data, annual_series_data, quarterly_series_data  = get_company_metrics(ticker)
+
+          # reformat all JSON returns to be flattened dictionaries 
+          ebitPerShare_dict = {'ebitPerShare': annual_series_data['ebitPerShare'][0]['v'] if 'ebitPerShare' in annual_series_data else 0}
+          ev_dict = {'ev' :annual_series_data['ev'][0]['v'] if 'ev' in annual_series_data else 0}
+          salesPerShare_dict = {'salesPerShare': annual_series_data['salesPerShare'][0]['v'] if 'salesPerShare' in annual_series_data else 0}
+          operatingMargin_dict = {'operatingMargin': annual_series_data['operatingMargin'][0]['v'] if 'operatingMargin' in annual_series_data else 0}
+          eps_dict = {'eps' :annual_series_data['eps'][0]['v'] if 'eps' in annual_series_data else 0}
+          pe_dict = {'pe': annual_series_data['pe'][0]['v'] if 'pe' in annual_series_data else 0}
+          ps_dict = {'ps': annual_series_data['ps'][0]['v'] if 0 in annual_series_data['ps'] else 0}
+          pb_dict = {'pb': annual_series_data['pb'][0]['v'] if 'pb' in annual_series_data else 0}
+
+          # merge all dictionary keys per ticker
+          combined_info = basic_info.copy()  # Make a copy of the basic info
+          combined_info = combined_info | metric_data | ebitPerShare_dict | ev_dict | salesPerShare_dict | operatingMargin_dict | eps_dict | pe_dict | ps_dict | pb_dict
+          
+          hash_map[ticker] = combined_info
+          
+          # equity gains
+          _, div, close_price = get_equity_gains(ticker=ticker, period=1810)
+          gains_data[ticker] = [div, close_price]
+      
+
+      # Now, create a DataFrame from the hash_map
+      df_1 = pd.DataFrame.from_dict(hash_map, orient='index')[['finnhubIndustry','pe','ps','pb','eps','epsGrowth5Y','ebitdPerShareAnnual', 'ebitdPerShareTTM', 'ebitdaCagr5Y', 'ebitdaInterimCagr5Y']]
+      df_2 = pd.DataFrame.from_dict(gains_data, orient='index', columns=['Recent Dividend','Price'])
+      df_final = df_1.join(df_2)
+
+      df_final['PE/G'] = df_final['pe'] / df_final['epsGrowth5Y']
+      df_final.rename({'finnhubIndustry':'Industry','pe':'P/E', 'ps':'P/S', 'pb':'P/B', 'eps': 'EPS'}, inplace=True, axis=1)
+      st.write(df_final)