65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
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import os
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import time
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import statistics
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import pandas as pd
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import numpy as np
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from pandas_datareader import data
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dir_path = os.path.dirname(os.path.realpath(__file__))
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start_date = '2014-01-01'
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end_date = '2018-01-01'
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SRC_DATA_FILENAME = 'goog_data.pkl'
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try:
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goog_data = pd.read_pickle(SRC_DATA_FILENAME)
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print('File data found...reading GOOG data')
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except FileNotFoundError:
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print('File not found...downloading the GOOG data')
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goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
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goog_data.to_pickle(SRC_DATA_FILENAME)
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goog_data_signal = pd.DataFrame(index=goog_data.index)
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goog_data_signal['price'] = goog_data['Adj Close']
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exe_start_time = time.time()
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import statistics as stats
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time_period = 20 # number of days over which to average
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history = [] # to track a history of prices
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sma_values = [] # to track simple moving average values
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for close_price in goog_data_signal['price']:
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history.append(close_price)
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if len(history) > time_period:
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# we remove oldest price because we only average over last 'time_period' prices
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# i.e. keep the latest 20 day window
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del(history[0])
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sma_values.append(stats.mean(history))
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# The first 20 sma of this data will not be mean of 20 values
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print("--- algo1: %s seconds ---" % (time.time() - exe_start_time))
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exe_start_time = time.time()
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sma_values_improved = goog_data_signal.rolling(window=20, win_type='boxcar').mean()
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print("--- algo2: %s seconds ---" % (time.time() - exe_start_time))
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goog_data = goog_data.assign(ClosePrice=pd.Series(goog_data_signal['price'], index=goog_data.index))
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goog_data = goog_data.assign(Simple20DayMovingAverage=pd.Series(sma_values, index=goog_data.index))
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goog_data = goog_data.assign(Simple20DayMovingAverage_pd = sma_values_improved)
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close_price = goog_data['ClosePrice']
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sma = goog_data['Simple20DayMovingAverage']
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import matplotlib.pyplot as plt
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fig = plt.figure()
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ax1 = fig.add_subplot(111, ylabel='Google price in $')
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close_price.plot(ax=ax1, color='g', lw=2., legend=True)
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sma.plot(ax=ax1, color='r', lw=2., legend=True)
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goog_data['Simple20DayMovingAverage_pd'].plot(ax=ax1, color='b', lw=1., legend=True)
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plt.savefig(dir_path+'/sma.png')
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plt.show()
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