[matplotlib]S5_07_histogram

crypto_daily_returns.csv

0.14MB

 

 

 

In [39]:

import pandas as pd
import matplotlib.pyplot as plt
import datetime

 

In [45]:

# 일별 수익률 데이터
return_df = pd.read_csv('crypto_daily_returns.csv'); return_df

 

Out[45]:

	Date	BTC	ETH	LTC
0	09/17/2014	0.000000	0.000000	0.000000
1	09/18/2014	-7.192558	NaN	-7.379983
2	09/19/2014	-6.984265	NaN	-7.629499
3	09/20/2014	3.573492	NaN	-0.955003
4	09/21/2014	-2.465854	NaN	-0.945300
...	...	...	...	...
2479	07/01/2021	-4.191449	-7.075787	-4.550086
2480	07/02/2021	0.967856	1.723823	-0.460711
2481	07/03/2021	2.276009	3.538258	2.436037
2482	07/04/2021	1.786156	4.294922	3.297811
2483	07/05/2021	-4.369154	-5.303886	-4.715207

2484 rows × 4 columns

 

In [55]:

# A histogram represents data using bars with various heights
mu = round(return_df['BTC'].mean(),2);print('mu:',mu)
sigma = round(return_df['BTC'].std(),2);print('sigma:',sigma)

 

 

mu: 0.25
sigma: 3.93

 

In [56]:

plt.figure(figsize=(12,6))
return_df['BTC'].plot.hist(bins=50, alpha = 0.5)
plt.grid()
plt.title('Histogram: mu= '+ str(mu) + ' sigma= ' + str(sigma))

 

Out[56]:

Text(0.5, 1.0, 'Histogram: mu= 0.25 sigma= 3.93')