text: import pandas as pd
  import yfinance as yf
  import numpy as np
  import csv as csv
  
  # Year - Month - Day
  start = '2020-01-01'
  end = '2020-05-22'
  interval = '1d'
  
  df = pd.read_csv('/home/chase/repos/NN_Predicting/sp500/S&P500-Symbols.csv', names=['Symbol'])
  inputfile = df['Symbol']
  
  inputm = []
  
  with open(inputfile, "rb") as f:
      reader = csv.reader(f, delimiter="\t")
      for row in reader:
          inputm.append(row)
  
  '''
  with open('/home/chase/repos/NN_Predicting/sp500/S&P500-Symbols.csv', 'rb') as f_input:
      csv_input = csv.reader(f_input)
      header = next(csv_input)
      data = zip(*[map(int, row) for row in csv_input])
  
  print(data.head())
  
  df = pd.DataFrame.from_csv('/home/chase/repos/NN_Predicting/sp500/S&P500-Symbols.csv', names=['Symbols'])
  rows = df.apply(lambda x: x.tolist(), axis=1)
  
  tickers = csv_array[0]
  
  
  list = np.asarray(inputm)
  
  data = yf.download(list, start=start, end=end, interval=interval, auto_adjust=True)
  '''
  print(inputm)