59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
|
# Same method as in sma.py, used pandas.DataFrame.rolling for faster calculation
|
||
|
|
|
||
|
|
import time
|
||
|
|
import statistics
|
||
|
|
import pandas as pd
|
||
|
|
import numpy as np
|
||
|
|
from pandas_datareader import data
|
||
|
|
|
||
|
|
exe_start_time = time.time()
|
||
|
|
|
||
|
|
start_date = '2014-01-01'
|
||
|
|
end_date = '2018-01-01'
|
||
|
|
SRC_DATA_FILENAME = 'goog_data.pkl'
|
||
|
|
|
||
|
|
try:
|
||
|
|
goog_data = pd.read_pickle(SRC_DATA_FILENAME)
|
||
|
|
print('File data found...reading GOOG data')
|
||
|
|
except FileNotFoundError:
|
||
|
|
print('File not found...downloading the GOOG data')
|
||
|
|
goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
|
||
|
|
goog_data.to_pickle(SRC_DATA_FILENAME)
|
||
|
|
|
||
|
|
goog_data_signal = pd.DataFrame(index=goog_data.index)
|
||
|
|
goog_data_signal['price'] = goog_data['Adj Close']
|
||
|
|
|
||
|
|
import statistics as stats
|
||
|
|
|
||
|
|
time_period = 20 # number of days over which to average
|
||
|
|
history = [] # to track a history of prices
|
||
|
|
sma_values = [] # to track simple moving average values
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
goog_data = goog_data.assign(ClosePrice=pd.Series(close, index=goog_data.index))
|
||
|
|
goog_data = goog_data.assign(Simple20DayMovinigAverage=pd.Series(result, index=goog_data.index))
|
||
|
|
print(result)
|
||
|
|
|
||
|
|
|
||
|
|
# for close_price in close:
|
||
|
|
# history.append(close_price)
|
||
|
|
# if len(history) > time_period: # we remove oldest price because we only average over last 'time_period' prices
|
||
|
|
# del(history[0])
|
||
|
|
# sma_values.append(stats.mean(history))
|
||
|
|
|
||
|
|
# goog_data = goog_data.assign(ClosePrice=pd.Series(close, index=goog_data.index))
|
||
|
|
# goog_data = goog_data.assign(Simple20DayMovingAverage=pd.Series(sma_values, index=goog_data.index))
|
||
|
|
# close_price = goog_data['ClosePrice']
|
||
|
|
# sma = goog_data['Simple20DayMovingAverage']
|
||
|
|
|
||
|
|
# print("--- %s seconds ---" % (time.time() - exe_start_time))
|
||
|
|
|
||
|
|
# import matplotlib.pyplot as plt
|
||
|
|
|
||
|
|
# fig = plt.figure()
|
||
|
|
# ax1 = fig.add_subplot(111, ylabel='Google price in $')
|
||
|
|
# close_price.plot(ax=ax1, color='g', lw=2., legend=True)
|
||
|
|
# sma.plot(ax=ax1, color='r', lw=2., legend=True)
|
||
|
|
# plt.savefig('sma.png')
|