def drawBuyA(row, col, symbols, start, end):
fig = plt.figure(figsize=(16, 16))
i = 0
for symbol in symbols:
print(symbol)
i += 1
data = TushareStore.get_a_daily_data_ind(table='a_daily',
symbol=symbol,
start_date=start,
end_date=end,
append_ind=True)
close, pdi, wr, wr_89, bias = data['close'], data['pdi'], data[
'willr'], data['willr_89'], data['bias']
ax = fig.add_subplot(row, col, i)
ax.plot(close, c='grey')
# buy = close[ind.LESS_THAN(bias.shift(1), -13) & ind.BOTTOM(bias)]
buy = close[ind.LESS_THAN(wr.shift(1), -88) & ind.BOTTOM(wr)]
# print buy
ax.scatter(buy.index, buy, s=20, c='green')
ax.set_xticks([])
ax.set_yticks([])
ax.set_ylabel(symbol)
plt.legend()
plt.subplots_adjust(hspace=1)
plt.show()
def drawBuy(row, col, sector, symbols, start, end):
fig = plt.figure(figsize=(16, 8))
i = 0
for symbol in symbols:
i += 1
data = TushareStore.get_usa_daily_data_ind(sector=sector,
symbol=symbol,
start_date=start,
end_date=end,
append_ind=True)
# data = store.get_chart_data_from_db("600%d.SH" % code, '20180101')
# data = get_chart_data_from_web(code, '1/1/2018', '1/30/2019')
close, pdi, wr, wr_89, bias = data['close'], data['pdi'], data[
'willr'], data['willr_89'], data['bias']
ax = fig.add_subplot(row, col, i)
ax.plot(close, c='grey')
# buy = close[(wr <= -98)]
# ax.scatter(buy.index, buy, c='red')
# buy = close[(wr <= -93) & (wr > -98)]
# ax.scatter(buy.index, buy, c='orange')
# buy = close[(wr <= -88) & (wr > -93)]
# ax.scatter(buy.index, buy, c='yellow')
# buy = close[(wr <= -83) & (wr > -88)]
# ax.scatter(buy.index, buy, c='green')
# buy = close[(pdi <= 10) & (wr < -88)]
# ax.scatter(buy.index, buy, c='red')
# buy = close[(pdi <= 12) & (pdi > 10) & (wr < -88)]
# ax.scatter(buy.index, buy, c='orange')
# buy = close[(pdi <= 16) & (pdi > 12) & (wr < -88)]
# ax.scatter(buy.index, buy, c='yellow')
# buy = close[(pdi <= 20) & (pdi > 16) & (wr < -88)]
# ax.scatter(buy.index, buy, c='green')
# buy = close[ind.UP_CROSS(wr_89, -83.5) & ind.LESS_THAN(wr, -50)]
# buy = close[ind.LESS_THAN(wr_89, -97) & ind.BOTTOM(wr_89)]
# buy = close[ind.LESS_THAN(bias, -12) & ind.BOTTOM(bias) & ind.LESS_THAN(wr_89, -83.5)]
buy = close[ind.LESS_THAN(bias.shift(1), -13) & ind.BOTTOM(bias)]
ax.scatter(buy.index, buy, s=20, c='green')
# ax = plt.twinx()
# ax.plot(bias)
# ax.plot(wr)
# drawHline(ax, [-12])
ax.set_xticks([])
ax.set_yticks([])
ax.set_ylabel(symbol)
plt.legend()
plt.subplots_adjust(hspace=0.1)
plt.show()
def drawMINMAX(ax, data, periods=[20]):
for period in periods:
if data.__contains__('min_%d' % period) & data.__contains__(
'max_%d' % period):
min = data['min_%d' % period]
max = data['max_%d' % period]
# elif data.__contains__('min') & data.__contains__('max'):
# min = data['min']
# max = data['max']
else:
close = data['close']
min = ind.MIN(close, period)
max = ind.MAX(close, period)
ax.plot(min, label='min%d' % period, linewidth=1)
ax.plot(max, label='max%d' % period, linewidth=1)
ax.set_ylabel('MIN_MAX')
def drawDMI(ax, data, periods=[6, 14], hlines=[10, 12, 16, 20, 22]):
if data.__contains__('pdi') & data.__contains__('mdi') & data.__contains__(
'adx') & data.__contains__('adxr'):
pdi = data['pdi']
mdi = data['mdi']
adx = data['adx']
adxr = data['adxr']
else:
close, high, low = data['close'], data['high'], data['low']
pdi, mdi = ind.DI(high, low, close, time_period=periods[0])
adx = ind.ADX(high, low, close, time_period=periods[1])
adxr = ind.ADXR(high, low, close, time_period=periods[1])
ax.plot(pdi, label='pdi%d' % periods[0])
# ax.plot(mdi, label='mdi%d' % periods[0])
# ax.plot(adx, label='adx%d' % periods[1])
# ax.plot(adxr, label='adxr%d' % periods[1])
drawHline(ax, hlines)
ax.set_ylabel('DMI')
def drawOBV(ax, data, hlines=[]):
if data.__contains__('obv'):
obv = data['obv']
else:
close, volume = data['close'], data['volume']
obv = ind.OBV(close, volume)
ax.plot(obv, label='obv')
drawHline(ax, hlines)
ax.set_ylabel('OBV')
def drawCCI(ax, data, periods=[14], hlines=[-231, -138, -110, -83, 50]):
for period in periods:
if data.__contains__('cci'):
cci = data['cci']
else:
close, high, low = data['close'], data['high'], data['low']
cci = ind.CCI(high, low, close, time_period=period)
ax.plot(cci, label='cci%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('CCI')
def drawSMA(ax, data, periods=[5, 10, 20, 30, 60, 120]):
for period in periods:
if data.__contains__('sma_%d' % period):
sma = data['sma_%d' % period]
elif data.__contains__('sma'):
sma = data['sma']
else:
close = data['close']
sma = ind.SMA(close, period)
ax.plot(sma, label='sma_%d' % period, linewidth=1)
def drawEMA(ax, data, periods=[5, 10, 20, 30, 60, 120]):
for period in periods:
if data.__contains__('ema%d' % period):
ema = data['ema%d' % period]
elif data.__contains__('ema'):
ema = data['ema']
else:
close = data['close']
ema = ind.SMA(close, period)
ax.plot(ema, label='ema%d' % period)
def save_industry_sat():
industry_sats = pd.DataFrame()
basic_stock = query_basic_stock()
print(basic_stock.head(5))
i = 0
for industry in basic_stock['industry'].unique():
i = i + 1
symbols = basic_stock[basic_stock['industry'] == industry]['ts_code']
industry_sat = pd.DataFrame()
for symbol in symbols:
print(symbol)
# try:
data = query_a_daily_data_ind(symbol=symbol,
trade_date='',
start_date='2019-01-01',
end_date='2019-04-30')
sat = ind.sat(data)
sat['symbol'] = symbol
industry_sat = industry_sat.append(sat)
industry_sat = industry_sat.sort_values(by=['pct_sum_90_max'],
ascending=False)
# except:
# print 'error', symbol
# print industry_top
industry_sats = industry_sats.append(industry_sat)
basic_stock['symbol'] = basic_stock['ts_code']
industry_sats = pd.merge(basic_stock,
industry_sats,
on=['symbol'],
how='inner')
industry_sats.to_csv('industry_sats.csv')
engine = create_engine(
'mysql://*****:*****@127.0.0.1:3306/Stock?charset=utf8')
# industry_sats.to_sql('industry_sats', engine, if_exists='append', index=False)
industry_sats_1 = industry_sats[0:1000]
industry_sats_1.to_sql('industry_sats',
engine,
if_exists='append',
index=False)
industry_sats_2 = industry_sats[1000:2000]
industry_sats_2.to_sql('industry_sats',
engine,
if_exists='append',
index=False)
industry_sats_3 = industry_sats[2000:3000]
industry_sats_3.to_sql('industry_sats',
engine,
if_exists='append',
index=False)
industry_sats_4 = industry_sats[3000:]
industry_sats_4.to_sql('industry_sats',
engine,
if_exists='append',
index=False)
def drawWR(ax, data, periods=[6, 89], hlines=[-98, -83.5, -25, -11]):
for period in periods:
if data.__contains__('willr_%d' % period):
willr = data['willr_%d' % period]
elif data.__contains__('willr'):
willr = data['willr']
else:
close, high, low = data['close'], data['high'], data['low']
willr = ind.WILLR(high, low, close, time_period=period)
ax.plot(willr, label='wr%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('WR')
def drawRSI(ax, data, periods=[6, 12, 24], hlines=[20, 50, 80]):
for period in periods:
if data.__contains__('rsi%d' % period):
rsi = data['rsi%d' % period]
elif data.__contains__('rsi'):
rsi = data['rsi']
else:
price = data['close']
rsi = ind.RSI(price, time_period=period)
ax.plot(rsi, label='rsi%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('RSI')
def drawROC(ax, data, periods=[14], hlines=[]):
for period in periods:
if data.__contains__('roc%d' % period):
roc = data['roc%d' % period]
elif data.__contains__('roc'):
roc = data['roc']
else:
price = data['close']
roc = ind.ROC(price, time_period=period)
ax.plot(roc, label='roc%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('ROC')
def drawTRIX(ax, data, periods=[14], hlines=[]):
for period in periods:
if data.__contains__('trix%d' % period):
trix = data['rsi%d' % period]
elif data.__contains__('trix'):
trix = data['trix']
else:
price = data['close']
trix = ind.TRIX(price, time_period=period)
ax.plot(trix, label='trix%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('TRIX')
def drawEMV(ax, data, periods=[14], hlines=[]):
for period in periods:
if data.__contains__('emv%d' % period):
emv = data['emv%d' % period]
elif data.__contains__('emv'):
emv = data['emv']
else:
low, high, volume = data['low'], data['high'], data['volume']
emv = ind.EMV(low, high, volume, time_period=period)
ax.plot(emv, label='emv%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('EMV')
def drawMFI(ax, data, periods=[14], hlines=[]):
for period in periods:
if data.__contains__('mfi%d' % period):
mfi = data['mfi%d' % period]
elif data.__contains__('mfi'):
mfi = data['mfi']
else:
high, low, close, volume = data['low'], data['high'], data[
'close'], data['volume']
mfi = ind.MFI(high, low, close, volume, time_period=period)
ax.plot(mfi, label='mfi%d' % period)
drawHline(ax, hlines)
ax.set_ylabel('MFI')
def drawBBANDS(ax, data, period=20):
if data.__contains__('upper_band') & data.__contains__(
'middle_band') & data.__contains__('lower_band'):
upper_band = data['upper_band']
middle_band = data['middle_band']
lower_band = data['lower_band']
else:
close = data['close']
upper_band, middle_band, lower_band = ind.BBANDS(close,
time_period=period)
ax.plot(upper_band, label='upper_band')
ax.plot(middle_band, label='middle_band')
ax.plot(lower_band, label='lower_band')
def save_a_daily_data_ind(start_date, end_date):
engine = create_engine(
'mysql://*****:*****@127.0.0.1:3306/Stock?charset=utf8')
symbols = query_symbols()
for symbol in symbols:
data = query_a_daily_data(symbol,
trade_date='',
start_date=start_date,
end_date=end_date)
open, close, high, low, volume = data['open'], data['close'], data[
'high'], data['low'], data['volume']
ochl2ind = ind.ochl2buy(open, close, high, low, volume)
data = data.join(ochl2ind, how='left')
data.to_sql('a_daily_ind', engine, if_exists='append', index=False)
print(symbol, 'loaded')
def drawKDJ(ax, data, periods=[9, 3, 3], hlines=[-14, -3, 6.5, 17, 95]):
if data.__contains__('slow_k') & data.__contains__('slow_d'):
slow_k = data['slow_k']
slow_d = data['slow_d']
else:
close, high, low = data['close'], data['high'], data['low']
slow_k, slow_d = ind.STOCH(high,
low,
close,
fastk_period=periods[0],
slowk_period=periods[1],
slowd_period=periods[2])
ax.plot(slow_d, label='d')
ax.plot(slow_k, label='k')
ax.plot(3 * slow_k - 2 * slow_d, label='j')
drawHline(ax, hlines)
# ax.fill_between(time, 80, rsi, where=rsi >= 80, facecolor='green')
# ax.fill_between(time, 20, rsi, where=rsi <= 20, facecolor='red')
ax.set_ylabel('KDJ')
def get_chart_data_from_web(code, start_date='', end_date='', append_ind=True):
data = web.DataReader(code,
data_source='yahoo',
start=start_date,
end=end_date)
data.rename(columns={
'Open': 'open',
'Close': 'close',
'High': 'high',
'Low': 'low',
'Volume': 'volume'
},
inplace=True)
if append_ind:
open, close, high, low, volume = data['open'], data['close'], data[
'high'], data['low'], data['volume']
ochl2ind = ind.ochl2ind(open, close, high, low, volume)
data = data.join(ochl2ind, how='left')
data['date'] = data.index
data['date'].apply(lambda date: date.date())
data.index = np.arange(0, 0 + len(data))
return data
def show_buy(ax, data, type):
close, low, high = data['close'], data['low'], data['high']
ma3, ma5, ma20, ma60 = data['sma_3'], data['sma_5'], data['sma_20'], data[
'sma_60']
diff, dea = data['dif'], data['dea']
close, willr, willr_34, willr_89, = data['close'], data['willr'], data[
'willr_34'], data['willr_89']
bias, pdi = data['bias'], data['pdi']
buy = ind.LESS_THAN(willr, -88)
# & ind.LESS_THAN(willr_34, -88)
# ind.GREAT_THAN(bias, 3)
# & ind.GREAT_THAN(willr_89, -28)
# & ind.LESS_THAN(willr, -70)
# ind.LESS_THAN(bias.shift(1), -3) & ind.BOTTOM(bias) &
# & ind.GREAT_THAN(willr, -40)
# & ind.LESS_THAN(bias.shift(), 3)
# & ind.BOTTOM(willr)
# & ind.LESS_THAN(willr_34.shift(1), -88)
# & ind.BOTTOM(willr_34)
# & ind.LESS_THAN(willr_89.shift(1), -88)
# & ind.BOTTOM(willr_89)
buy = ind.TOUCH(close, ma20) & ind.TOUCH(diff, dea, 0.3)
# diff,dea 死叉 close>ma20 会上涨 close<ma20 会下跌
# 上升趋势 diff,dea,close,ma20 同时死叉 最佳买点 会涨
# 下跌趋势 diff,dea,close,ma20 同时金叉 反弹最高点，会跌
# 上升趋势 diff,dea,close,ma20 同时金叉 最佳买点 会涨
buy = ind.DEAD_CROSS(diff, dea)
# diff,dea 金叉，close>ma20 会震荡回调 close<ma20 会补涨
# 上升趋势 diff,dea,close,ma20 同时金叉 最佳买点 会涨
# 下跌趋势 diff,dea,close,ma20 同时金叉 反弹最高点，会跌
# buy = ind.GOLDEN_CROSS(diff, dea) | ind.DEAD_CROSS(diff, dea)
k_golden_cross = ind.GOLDEN_CROSS(close, ma20) | ind.GOLDEN_CROSS(
close, ma60)
k_dead_cross = ind.DEAD_CROSS(close, ma20) | ind.DEAD_CROSS(close, ma60)
macd_golden_cross = ind.GOLDEN_CROSS(diff, dea) | ind.UP_CROSS(diff, 0)
macd_dead_cross = ind.DEAD_CROSS(diff, dea) | ind.DOWN_CROSS(diff, 0)
if type == 'k':
# ax.scatter(close[k_golden_cross].index, close[k_golden_cross], s=20, c='darkgoldenrod', zorder=200)
# ax.scatter(close[k_dead_cross].index, close[k_dead_cross], s=20, c='black', zorder=200)
ax.scatter(close[macd_golden_cross].index,
close[macd_golden_cross],
s=20,
c='darkgoldenrod',
zorder=200)
# ax.scatter(close[macd_dead_cross].index, close[macd_dead_cross], s=20, c='black', zorder=200)
else:
# ax.scatter(diff[k_golden_cross].index, diff[k_golden_cross], s=20, c='darkgoldenrod', zorder=200)
# ax.scatter(diff[k_dead_cross].index, diff[k_dead_cross], s=20, c='black', zorder=200)
ax.scatter(diff[macd_golden_cross].index,
diff[macd_golden_cross],
s=20,
c='darkgoldenrod',
zorder=200)
def show_trend(ax, data):
close, low, high = data['close'], data['low'], data['high']
ma3, ma5, ma20, ma60 = data['sma_3'], data['sma_5'], data['sma_20'], data[
'sma_60']
diff, dea, hist = data['dif'], data['dea'], data['hist']
ax = plt.twinx()
ax.set_yticks([])
condition_up = (ind.UP(ma3) | ind.UP(ma20)) & (ind.UP(diff) | ind.UP(dea))
condition_up = ind.UP(dea)
condition_down = (ind.DOWN(ma3) | ind.DOWN(ma20)) & (ind.DOWN(diff)
| ind.DOWN(dea))
condition_down = ind.DOWN(dea)
# 强上涨
ax.bar(data[condition_up & ind.SEQ(0, dea, diff)].index,
1,
facecolor='darkred',
width=1,
alpha=0.7)
# ax.bar(data[ind.UP(close) & condition_up & ind.SEQ(0, dea, diff)].index, 1, facecolor='darkred', width=1, alpha=0.2)
# 弱上涨
ax.bar(data[condition_up & ind.SEQ(dea, diff, 0)].index,
1,
facecolor='darkred',
width=1,
alpha=0.2)
# # 努力上升
ax.bar(data[condition_up & ind.SEQ(dea, 0, diff)].index,
1,
facecolor='darkred',
width=1,
alpha=0.5)
# 强下跌
ax.bar(data[condition_down & ind.SEQ(diff, dea, 0)].index,
1,
facecolor='darkgreen',
width=1,
alpha=0.8)
# 弱下跌
ax.bar(data[condition_down & ind.SEQ(0, diff, dea)].index,
1,
facecolor='darkgreen',
width=1,
alpha=0.2)
# # 努力下跌
ax.bar(data[condition_down & ind.SEQ(diff, 0, dea)].index,
1,
facecolor='darkgreen',
width=1,
alpha=0.5)
# AMZN
# GOOG
# .HK .SZ .HZ
# 300059.sz
# pdi 10~20 13~16
# mdi
data = web.DataReader('300059.sz',
data_source='yahoo',
start='1/1/2018',
end='1/30/2019')
data = pd.DataFrame(data)
high, low, close, volume = data['High'], data['Low'], data['Close'], data[
'Volume']
pdi, mdi = ind.DI(high, low, close, time_period=14)
adx = ind.ADX(high, low, close, time_period=6)
upper_band, middle_band, lower_band = ind.BBANDS(close, time_period=20)
m, s, macd_histogram = ind.MACD(close,
fast_period=12,
slow_period=26,
signal_period=9)
rsi = ind.RSI(close, time_period=14)
min = ind.MIN(close, 20)
max = ind.MAX(close, 50)
df = pd.DataFrame()
df['close'] = close
df['fast'] = m
df['slow'] = s
df['ref'] = df['fast'].shift(1) < df['slow'].shift(1)
