text: import numpy as np
  import pandas_datareader as pdr
  import datetime as dt
  import pandas as pd
  import matplotlib.pyplot as plt
  
  from get_data_api_b import get_pd_daily_histo
  
  
  start = dt.datetime(2020, 9, 1)
  symbol = 'BTCUSDT'
  
  date_in_string = start.strftime("%d %b %Y ") 
  data = get_pd_daily_histo(symbol, date_in_string)
  data = data.set_index('Open_Time')
  
  high_low = data['High'] - data['Low']
  high_cp = np.abs(data['High'] - data['Close'].shift())
  low_cp = np.abs(data['Low'] - data['Close'].shift())
  
  df = pd.concat([high_low, high_cp, low_cp], axis=1)
  true_range = np.max(df, axis=1)
  average_true_range = true_range.rolling(14).mean()
  
  fig, ax = plt.subplots()
  average_true_range.plot(ax=ax)
  ax2 = data['Close'].plot(ax=ax, secondary_y=True, alpha=.3)
  ax.set_ylabel("ATR")
  ax2.set_ylabel("Price")
  
  plt.show()