test.py

# import pandas as pd
import os
import time
from datetime import datetime

from time import mktime

import matplotlib
import matplotlib.pyplot as plt
from matplotlib import style
style.use("dark_background")

import re


path = "intraQuarter"

def Key_Stats(gather="Total Debt/Equity (mrq)"):
	statspath = path + "/_KeyStats"
	stock_list = [x[0] for x in os.walk(statspath)]
	df = pd.DataFrame(columns=["Date",
							   "Unix",
							   "Ticker",
							   "DE Ratio",
							   "Price",
							   "stock_p_change",
							   "SP500",
							   "sp500_p_chang"
							   "Difference"])
	# print(stock_list)

	sp500_df = pd.DataFrame.from_csv("YAHOO-INDEX_SPY.csv")

	ticker_list = []

	for each_dir in stock_list[1:]:
		each_file = os.listdir(each_dir)
		ticker = each_dir.split("/")[2]
		ticker_list.append(ticker)


		starting_stock_value = False
		starting_sp500_value = False


		if len(each_file) > 0 :
			for file in each_file:
				data_stamp = datetime.strptime(file , "%Y%m%d%H%M%S.html")
				unix_time = time.mktime(data_stamp.timetuple())
				# print(data_stamp, unix_time)
				full_file_path = each_dir+"/"+file
				# print(full_file_path)
				source = open(full_file_path, "r").read()
				try:
					value = float(source.split(gather+':</td><td class="yfnc_tabledata1">')[1].split('</td>')[0])

					try:
						sp500_date = datetime.fromtimestamp(unix_time).strftime("%Y-%m-%d")
						row = sp500_df[(sp500_df.index == sp500_date)]
						sp500_value = float(row["Adjusted Close"])

					except:
						sp500_date = datetime.fromtimestamp(unix_time - (60*60*24*3)).strftime("%Y-%m-%d")
						row = sp500_df[(sp500_df.index == sp500_date)]
						sp500_value = float(row["Adjusted Close"])

					stock_price = float(source.split("</small><big><b>")[1].split("</b></big>")[0])
					# print("stock price: ",stock_price, "ticker: ", ticker)

					if not starting_stock_value:
						starting_stock_value = stock_price

					if not starting_sp500_value:
						starting_sp500_value = sp500_value

					stock_p_change = ((stock_price - starting_stock_value) / starting_stock_value) * 100
					sp500_p_change = ((sp500_value - starting_sp500_value) / starting_sp500_value) * 100


					df = df.append({"Date": data_stamp,
									"Unix": unix_time,
									"Ticker": ticker,
									"DE Ratio": value,
									"Price": stock_price,
									"stock_p_change": stock_p_change,
									"sp500": sp500_value,
									"sp500_p_change": sp500_p_change,
									"Difference": stock_p_change-sp500_p_change}, ignore_index=True)

				except Exception as e:
					pass

	for each_ticker in ticker_list:
		try:
			plot_df = df[(df["Ticker"] == each_ticker)]
			plot_df = plot_df.set_index(["Date"])

			plot_df["Difference"].plot(label=each_ticker)
			plt.legend()

		except:
			pass


	plt.show()


	# save = gather.replace(" ", "").replace("(", "").replace(")", "").replace("/", "")+(".csv")
	# df.to_csv(save)

Key_Stats()