Update EOD_charts.py

EOD_charts.py

@@ -16,16 +16,16 @@
 import pandas as pd
 import numpy as np
 import re
-import plotly
 import requests
 from datetime import timedelta
 
 import dash
 import dash_html_components as html
 import dash_core_components as dcc
 from dash.dependencies import Output, Input
-import plotly.tools as tls
 
+import plotly
+import plotly.tools as tls
 
 from subprocess import run, PIPE
 from io import StringIO
@@ -65,6 +65,8 @@
  [Input('stock_input', 'value')]
  )
 def cache(stock):
+ # The '.NS' is for NSE stocks, for other exchange stocks just input the correct extension ,
+ # that is available from Yahoo Finance.
  df = download_quotes(stock+'.NS', write_to_file = False)
  df = df.dropna()
  df = df.reset_index(drop = True)
@@ -127,7 +129,7 @@ def gr2(json_data,graphtype):
  df['LowerBand'] = df['20 DMA']-(df['Adj Close'].rolling(window=20).std()*2)
 
 
- if graphtype==1: # Bollinger bands
+ if graphtype==1: # Bollinger bands indicator
  traces1 = []
 
  traces1.append(plotly.graph_objs.Scatter(x = df.DateTime, y = df['Adj Close'], 
@@ -145,7 +147,13 @@ def gr2(json_data,graphtype):
 
  return {'data': traces1, 'layout':layout1}
 
- elif graphtype==2: # Swing
+ elif graphtype==2: # Swing level indicator
+
+ # This indicator is got from https://www.vfmdirect.com/kplswing/index.html
+ # The souce code for this - https://www.vfmdirect.com/kplswing/kpl_swing.afl
+ # 
+ # In simple words this is a break-out trading strategy.
+
  res=df['High'].rolling(window= 20).max()
  sup=df['Low'].rolling(window= 20).min()