tfci_prepare_btc_ds.py

import datetime
import pandas_datareader as pdr
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd


btc_data = pdr.get_data_yahoo(['BTC-USD'], 
                              start=datetime.datetime(2018, 1, 1), 
                              end=datetime.datetime(2020, 12, 3))['Close']
btc_data = btc_data.reset_index().drop_duplicates(subset='Date', keep='last').set_index('Date').sort_index()
btc_data = btc_data.resample('D').fillna('nearest')
X_data = pdr.get_data_yahoo(['TWTR', 'GOOGL', 'AAPL', 'MSFT', 'AMZN', 'FB', 'GOLD'], 
                            start=datetime.datetime(2018, 1, 1), 
                            end=datetime.datetime(2020, 12, 2))['Close']
X_data = X_data.reset_index().drop_duplicates(subset='Date', keep='last').set_index('Date').sort_index()
X_data = X_data.resample('D').fillna('nearest')
data = pd.concat([btc_data, X_data], axis=1)
data.dropna(inplace=True)
data = data.resample('W-Wed').last()  # Weekly is easier to process. We select Wednesday to 2020-10-21 is available.
data = data.astype(np.float32)

np.log(data).plot(figsize=(15, 12))
plt.axvline('2020-10-14', 0, np.max(data['BTC-USD']), lw=2, ls='--', c='red', label='PayPal Impact')
plt.legend(loc='upper left')