5 day moving average closing price: from the fifth day, calculate an average of the closing price of the latest line constituted daily five days.
Moving average algorithm:
(a+b+c+d+e)/5 (b+c+d+e+f)/5 (c+d+e+f+g)/5 ... (f+g+h+i+j)/5
Drawing 5. 10 MA K line graph in FIG.
# Moving Average Import numpy AS NP Import matplotlib.pyplot AS MP Import datetime dt AS Import matplotlib.dates AS md DEF dmy2ymd (dmy): "" " The sun and the moon in turn date : param Day: : return: " " " DMY = STR (DMY, encoding = ' UTF-. 8 ' ) T = dt.datetime.strptime (DMY, ' %% D- M-% the Y ' ) S = t.date (). the strftime ( ' % Y- M-% D% ' ) return S a dates, opening_prices, \ highest_prices, lowest_prices, \ closing_prices = \ Np.loadtxt ( ' aapl.csv ' , DELIMITER = ' , ' , usecols = (. 1,. 3,. 4,. 5,. 6 ), the unpack = True, DTYPE = ' M8 [D], F8, F8, F8, F8 ' , Converters = {. 1: dmy2ymd}) # DMY transfer date Print (a dates) # drawn closing price discount FIG mp.figure ( ' APPL ' , facecolor = ' LightGray ') Mp.title ( ' APPL ' , 18 is fontSize = ) mp.xlabel ( ' a Date ' , fontSize = 14 ) mp.ylabel ( ' Price ' , fontSize = 14 ) mp.grid (lineStyle = " : " ) # Set Scale Locator # weekly main scale a day, a time scale AX = mp.gca () ma_loc = md.WeekdayLocator (byweekday = md.MO) ax.xaxis.set_major_locator (ma_loc) ax.xaxis.set_major_formatter (md.DateFormatter ( ' % Y-M-% D% ' )) ax.xaxis.set_minor_locator (md.DayLocator ()) # 修改dates的dtype为md.datetime.datetiem dates = dates.astype(md.datetime.datetime) mp.plot(dates, closing_prices, color='dodgerblue', linewidth=2, linestyle='--', alpha=0.8, label='APPL Closing Price') #绘制5日移动平均线 ma5 = np.zeros(closing_prices.size-4) for i in range(ma5.size): ma5[i] =np.mean(closing_prices[i:i+5]) mp.plot(dates[4:],ma5,color='orangered',label='MA5') #绘制10日移动平均线 ma10 = np.zeros(closing_prices.size-9) for i in range(ma10.size): ma10[i] =np.mean(closing_prices[i:i+10]) mp.plot(dates[9:],ma10,color='green',label='MA10') mp.legend() mp.gcf().autofmt_xdate() mp.show()
