Historical Data of Ardor (ARDR)

From 28 April 2013 to datetime.datetime.today().



In [1]:

    
import datetime

import pandas as pd
import numpy as np
from fbprophet import Prophet



In [2]:

    
dfs = pd.read_html('https://coinmarketcap.com/currencies/ardor/historical-data/?start=20130428&end={}'.format(datetime.datetime.today().strftime('%Y%m%d')))

df = dfs[0]

df.tail()









    Out[2]:







  
    
      
      Date
      Open
      High
      Low
      Close
      Volume
      Market Cap
    
  
  
    
      422
      Jul 31, 2016
      0.039315
      0.039423
      0.038534
      0.039141
      0
      -
    
    
      423
      Jul 30, 2016
      0.039250
      0.039641
      0.038929
      0.039318
      0
      -
    
    
      424
      Jul 25, 2016
      0.042403
      0.042463
      0.042117
      0.042117
      7
      -
    
    
      425
      Jul 24, 2016
      0.036912
      0.042547
      0.036834
      0.042405
      7
      -
    
    
      426
      Jul 23, 2016
      0.036725
      0.036970
      0.036284
      0.036970
      36
      -



In [3]:

    
df = df.drop(columns=['Open', 'High', 'Low', 'Volume', 'Market Cap'])
df = df.rename(columns={'Date': 'ds', 'Close': 'y'})

df.tail()









    Out[3]:







  
    
      
      ds
      y
    
  
  
    
      422
      Jul 31, 2016
      0.039141
    
    
      423
      Jul 30, 2016
      0.039318
    
    
      424
      Jul 25, 2016
      0.042117
    
    
      425
      Jul 24, 2016
      0.042405
    
    
      426
      Jul 23, 2016
      0.036970



In [4]:

    
df['y'] = np.log(df['y'])

df.tail()









    Out[4]:







  
    
      
      ds
      y
    
  
  
    
      422
      Jul 31, 2016
      -3.240585
    
    
      423
      Jul 30, 2016
      -3.236073
    
    
      424
      Jul 25, 2016
      -3.167304
    
    
      425
      Jul 24, 2016
      -3.160489
    
    
      426
      Jul 23, 2016
      -3.297649



In [5]:

    
m = Prophet()
m.fit(df)









    



INFO:fbprophet.forecaster:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.
INFO:fbprophet.forecaster:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.






    Out[5]:





<fbprophet.forecaster.Prophet at 0x10eeb5048>



In [6]:

    
future = m.make_future_dataframe(periods=365)
future.tail()



In [7]:

    
forecast = m.predict(future)
forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()



In [8]:

    
m.plot(forecast)









    Out[8]:



In [9]:

    
m.plot_components(forecast)









    Out[9]:



In [ ]:

	ds
787	2018-11-24
788	2018-11-25
789	2018-11-26
790	2018-11-27
791	2018-11-28

	ds	yhat	yhat_lower	yhat_upper
787	2018-11-24	1.731838	-3.381154	7.026396
788	2018-11-25	1.746593	-3.427866	7.025637
789	2018-11-26	1.771612	-3.431581	6.944436
790	2018-11-27	1.768283	-3.348127	7.073092
791	2018-11-28	1.783292	-3.434536	7.128455

	Date	Open	High	Low	Close	Volume	Market Cap
422	Jul 31, 2016	0.039315	0.039423	0.038534	0.039141	0	-
423	Jul 30, 2016	0.039250	0.039641	0.038929	0.039318	0	-
424	Jul 25, 2016	0.042403	0.042463	0.042117	0.042117	7	-
425	Jul 24, 2016	0.036912	0.042547	0.036834	0.042405	7	-
426	Jul 23, 2016	0.036725	0.036970	0.036284	0.036970	36	-

	ds	y
422	Jul 31, 2016	-3.240585
423	Jul 30, 2016	-3.236073
424	Jul 25, 2016	-3.167304
425	Jul 24, 2016	-3.160489
426	Jul 23, 2016	-3.297649