Limit plotting data

indicators.py

@@ -38,23 +38,23 @@ pd.options.mode.chained_assignment = None  # default='warn'
 load_dotenv()
 
 LB_YEAR = 3 # years of stock data to retrieve
-# PLT_YEAR = 2 # number of years data to plot
+PLT_YEAR = 2.7 # number of years data to plot
 LB_TRIGGER = 5 # days to lookback for triggering events
 
-def intelligent_loop_plots(sym, stk_data):
-    # Only plot ones that are standing out meaning:
-    #     1. outside of bollinger bands or recently crossed over (within 9 days)
-    #     2. RSI above 70 or below 30
-    #     3. VoRSI above 70 or below 30
-    #     4. when normalized MACD hist (by dividing slower moving average) is
-    #        above 2% or below -2%.
-    #     5. near golden cross or death cross
-    #     6. price cross (near) 200 day moving average
-    #     7. MACD histogram zero crossing (bullish or bearish)
+def intelligent_loop_plots(sym : str, stk_data):
+    """calculated indicators
 
-    # symbol = ['AMZN', 'SPY', 'GOOG', 'BAC', 'BA', 'XLE', 'CTL', 'ATVI', 'JD',\
-    #           'COST', 'HD', 'UBER', 'XOM', 'UAL', 'LUV', 'T', 'WMT']
+    Args:
+        sym (str): ticker
+        stk_data (DataFrame): stock data
 
+    Returns:
+        DataFrame: price
+        DataFrame: volume
+        DataFrame: macd
+        DataFrame: rsi
+        str: detected indicators
+    """
     price = stk_data["adjclose"]
     vol = stk_data["volume"]
     stk = security(sym, price, vol)
@@ -385,11 +385,15 @@ def update_graph(col_chosen):
 
     sym = col_chosen.split()[0]
     end_date = dt.datetime.today()
-    start_date = end_date - dt.timedelta(days = 365 * LB_YEAR)
-    # plot_sd = end_date - dt.timedelta(days = 365 * plt_year)
-    # plot_ed = end_date
+    start_date = end_date - dt.timedelta(days = round(365 * LB_YEAR))
+    days_to_drop = round(365 * (LB_YEAR-PLT_YEAR))
+    days_to_drop = days_to_drop if days_to_drop > 0 else 0
     tmp = fetch_stk_data(sym, start_date) # cached function all
     data, vol, macd, rsi, plot_ind = intelligent_loop_plots(sym, tmp)
+    data.drop(data.index[:days_to_drop], inplace=True)
+    vol.drop(vol.index[:days_to_drop], inplace=True)
+    macd.drop(macd.index[:days_to_drop], inplace=True)
+    rsi.drop(rsi.index[:days_to_drop], inplace=True)
 
     fig = make_subplots(
         rows=3,