In [1]:

    

import numpy as np # Linear Alg
import pandas as pd # CSV file I/O & data processing

# Visualization
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
import warnings 
from matplotlib import style
from matplotlib.finance import candlestick_ohlc
warnings.filterwarnings("ignore")
style.use('ggplot')

%matplotlib inline
plt.rcParams['figure.figsize'] = (12.0, 8.0)

from subprocess import check_output


    

    




/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/cbook.py:136: MatplotlibDeprecationWarning: The finance module has been deprecated in mpl 2.0 and will be removed in mpl 2.2. Please use the module mpl_finance instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)

In [2]:

    

data_dir = '../../input'
# Check what files our dataset contain
print('Our dataset contains the following files: \n')
print(check_output(["ls", data_dir]).decode("utf8"))


    

    




Our dataset contains the following files: 

bitcoin_cash_price.csv
bitcoin_dataset.csv
bitcoin_price.csv
bitconnect_price.csv
dash_price.csv
ethereum_classic_price.csv
ethereum_dataset.csv
ethereum_price.csv
iota_price.csv
litecoin_price.csv
monero_price.csv
nem_price.csv
neo_price.csv
numeraire_price.csv
omisego_price.csv
qtum_price.csv
ripple_price.csv
stratis_price.csv
waves_price.csv

In [3]:

    

ethereum_price = pd.read_csv('{}/ethereum_price.csv'.format(data_dir), parse_dates=['Date'], index_col=0)
ethereum_price.dtypes


    

    
Out[3]:





Open          float64
High          float64
Low           float64
Close         float64
Volume         object
Market Cap     object
dtype: object

In [4]:

    

#view the first fifteen rows
ethereum_price.head(15)


    

    
Out[4]:







  

    

      

      
Open
      
High
      
Low
      
Close
      
Volume
      
Market Cap
    
    

      
Date
      

      

      

      

      

      

    
  
  

    

      
2017-09-05
      
297.57
      
318.57
      
268.29
      
312.99
      
1,551,050,000
      
28,100,000,000
    
    

      
2017-09-04
      
347.13
      
347.13
      
279.94
      
295.17
      
1,801,690,000
      
32,774,000,000
    
    

      
2017-09-03
      
350.23
      
366.49
      
332.23
      
347.48
      
986,266,000
      
33,059,800,000
    
    

      
2017-09-02
      
387.82
      
389.35
      
328.10
      
348.98
      
1,483,600,000
      
36,601,200,000
    
    

      
2017-09-01
      
383.47
      
390.04
      
383.47
      
387.74
      
874,222,000
      
36,182,900,000
    
    

      
2017-08-31
      
378.44
      
386.14
      
376.35
      
383.04
      
706,254,000
      
35,701,500,000
    
    

      
2017-08-30
      
369.47
      
388.75
      
361.97
      
378.49
      
1,333,320,000
      
34,848,400,000
    
    

      
2017-08-29
      
347.96
      
373.76
      
347.79
      
370.67
      
1,220,030,000
      
32,813,200,000
    
    

      
2017-08-28
      
350.04
      
352.05
      
338.41
      
347.75
      
854,319,000
      
33,002,700,000
    
    

      
2017-08-27
      
334.36
      
347.89
      
334.36
      
347.89
      
633,370,000
      
31,517,500,000
    
    

      
2017-08-26
      
331.99
      
334.99
      
327.92
      
333.88
      
514,181,000
      
31,288,300,000
    
    

      
2017-08-25
      
326.11
      
336.40
      
325.80
      
331.92
      
760,329,000
      
30,727,900,000
    
    

      
2017-08-24
      
317.45
      
327.96
      
317.08
      
325.61
      
697,665,000
      
29,904,600,000
    
    

      
2017-08-23
      
315.27
      
324.21
      
314.54
      
317.52
      
811,990,000
      
29,691,900,000
    
    

      
2017-08-22
      
321.06
      
327.36
      
297.91
      
314.79
      
1,336,400,000
      
30,229,900,000
    
  

In [5]:

    

#view the last fifteen rows
ethereum_price.tail(15)


    

    
Out[5]:







  

    

      

      
Open
      
High
      
Low
      
Close
      
Volume
      
Market Cap
    
    

      
Date
      

      

      

      

      

      

    
  
  

    

      
2015-08-21
      
1.480000
      
1.560000
      
1.350000
      
1.400000
      
2,020,970
      
107,266,000
    
    

      
2015-08-20
      
1.250000
      
1.530000
      
1.250000
      
1.460000
      
2,843,760
      
90,809,000
    
    

      
2015-08-19
      
1.170000
      
1.320000
      
1.170000
      
1.260000
      
1,486,240
      
84,663,900
    
    

      
2015-08-18
      
1.220000
      
1.330000
      
1.090000
      
1.090000
      
1,485,680
      
88,143,200
    
    

      
2015-08-17
      
1.580000
      
1.580000
      
1.190000
      
1.200000
      
1,942,830
      
95,819,700
    
    

      
2015-08-16
      
1.680000
      
1.700000
      
1.090000
      
1.570000
      
3,550,790
      
102,028,000
    
    

      
2015-08-15
      
1.800000
      
1.880000
      
1.570000
      
1.690000
      
2,554,360
      
109,160,000
    
    

      
2015-08-14
      
1.810000
      
2.260000
      
1.750000
      
1.830000
      
4,637,030
      
109,594,000
    
    

      
2015-08-13
      
1.220000
      
1.970000
      
1.170000
      
1.830000
      
4,068,680
      
73,935,400
    
    

      
2015-08-12
      
1.060000
      
1.290000
      
0.883608
      
1.220000
      
2,150,620
      
64,018,400
    
    

      
2015-08-11
      
0.708087
      
1.130000
      
0.663235
      
1.070000
      
1,463,100
      
42,796,500
    
    

      
2015-08-10
      
0.713989
      
0.729854
      
0.636546
      
0.708448
      
405,283
      
43,130,000
    
    

      
2015-08-09
      
0.706136
      
0.879810
      
0.629191
      
0.701897
      
532,170
      
42,637,600
    
    

      
2015-08-08
      
2.790000
      
2.800000
      
0.714725
      
0.753325
      
674,188
      
167,911,000
    
    

      
2015-08-07
      
2.830000
      
3.540000
      
2.520000
      
2.770000
      
164,329
      
-
    
  

In [6]:

    

print('Date of newest data: {}'.format(ethereum_price.index[0]))
print('Date of oldest data: {}'.format(ethereum_price.index[-1]))


    

    




Date of newest data: 2017-09-05 00:00:00
Date of oldest data: 2015-08-07 00:00:00

In [7]:

    

eth_ohlc = ['Open', 'High', 'Low', 'Close']

for feat in eth_ohlc:
    print('---------------------------------------------')
    print('Statistics for Ethereum {} values:'.format(feat))
    print(ethereum_price[feat].describe())


    

    




---------------------------------------------
Statistics for Ethereum Open values:
count    761.000000
mean      49.895319
std       94.701419
min        0.431589
25%        4.360000
50%       11.110000
75%       17.360000
max      397.590000
Name: Open, dtype: float64
---------------------------------------------
Statistics for Ethereum High values:
count    761.000000
mean      52.372998
std       99.021937
min        0.482988
25%        4.770000
50%       11.340000
75%       18.880000
max      414.760000
Name: High, dtype: float64
---------------------------------------------
Statistics for Ethereum Low values:
count    761.000000
mean      47.483389
std       90.028103
min        0.420897
25%        4.030000
50%       10.750000
75%       16.370000
max      383.470000
Name: Low, dtype: float64
---------------------------------------------
Statistics for Ethereum Close values:
count    761.000000
mean      50.287726
std       95.157500
min        0.434829
25%        4.400000
50%       11.080000
75%       17.600000
max      401.490000
Name: Close, dtype: float64

In [8]:

    

# plotting the open, close, high, low of ethereum on in a line graph
for feat in eth_ohlc:
    plt.plot(ethereum_price[feat], label=feat)
    
plt.xlabel('Time(Yr-M)')
plt.ylabel('Value(USD)')
plt.legend()
plt.show()


    

In [9]:

    

#plotting with recent data of ethereum

n_days = 365 # number of recent days

for feature in eth_ohlc:
    plt.plot(ethereum_price[feature].iloc[:n_days], label=feature)

plt.title('Pricing Trend(last year)')
plt.xlabel('Time(Yr-M)')
plt.ylabel('Value(USD)')
plt.legend()
plt.show()


    

In [ ]: