def plot_candidate(s, lines):
fig = plt.figure(figsize=(12, 9))
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
_ax1 = plt.subplot(gs[0])
gs.update(left=0.05, right=0.48, hspace=0.0)
ax1 = plt.subplot(gs[1])
_gdfquotes = DataAPI.MktEqudAdjGet(ticker=s,
endDate=now,
field=[
u'secShortName', 'tradeDate',
'openPrice', 'highestPrice',
'lowestPrice', 'closePrice',
'turnoverVol'
],
isOpen=1)
_beginindex = max(len(_gdfquotes) - 60, 0)
print _gdfquotes[u'secShortName'].iloc[-1], v[0]
_ax1.set_title(u'%s' % (k[:6]), fontproperties=font, fontsize='16')
fig.sca(_ax1)
xg.plot_dragonpoint(_ax1, _gdfquotes, _beginindex, lines, 60)
#成交量
fig.sca(ax1)
xg.plot_volume_overlay(ax1, _gdfquotes, _beginindex)
ax1.yaxis.set_visible(False)
plt.show()
def plot_security_his(data, security_name):
security = data[data['ticker'] == security_name]
#reset figure for plot
fig = plt.figure(figsize=(12, 9))
gs = gridspec.GridSpec(2, 2, height_ratios=[4, 1], width_ratios=[3, 1])
gs.update(hspace=0.0)
ax0 = plt.subplot(gs[0, 0])
ax2 = plt.subplot(gs[1, 0])
ax1 = plt.subplot(gs[:, 1])
plt.sca(ax0)
plt.cla()
#plot title
ax0.set_title(
u'%s%s 回报%f' %
(security_name, security['name'].iloc[0], security['amount'].sum()),
fontproperties=font,
fontsize='16')
#plot candlestick graph
_dfquotes = mktgethis(security_name,
someday(str(security['tradeDate'].iloc[0]), -365),
someday(str(security['tradeDate'].iloc[-1]), 3), [
u'tradeDate', u'openPrice', u'highestPrice',
u'lowestPrice', u'closePrice', u'turnoverVol'
])
beginx = 0
_period = [(x.replace('-', '')) for x in _dfquotes['tradeDate']]
beginx = _period.index(str(security['tradeDate'].iloc[0]))
beginx = max(beginx - 20, 0)
xg.plot_security_k(ax0, _dfquotes, beginx)
plotbsp(_period[beginx:], security)
plt.grid()
#成交量
fig.sca(ax2)
xg.plot_volume_overlay(ax2, _dfquotes, beginx)
ax2.yaxis.set_visible(False)
plt.grid()
plottranlog(ax1, security)
plt.tight_layout() #to avoid the axis label is cut
plt.show()
plt.savefig('%s_his.svg' % (security_name))
pass
cols = []
for i in range(0, len(df)):
cols.append('%s封板开板%i次%s封死' % (firstzt[i], kbnumber[i], lastzt[i]))
df[u'涨跌停时间'] = cols
del df['highestPrice']
del df['secID']
dfsort = df.sort_values([u'涨跌停次数', u'涨跌停时间'], ascending=[False, True])
dfsort.to_excel('dailyreview.xlsx')
#plot da pang K线图
fig = plt.figure(figsize=(12, 9))
fig.set_size_inches(24, 18)
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1])
_ax1 = plt.subplot(gs[0])
gs.update(left=0.05, right=0.48, hspace=0.0)
ax1 = plt.subplot(gs[1])
_his.columns = [
u'secShortName', 'tradeDate', 'openPrice', 'highestPrice', 'lowestPrice',
'closePrice', 'turnoverVol'
]
_beginindex = max(len(_his) - 120, 0)
#_ax1.set_title('%s'%(_his['secShortName'].iloc[-1]),fontproperties=font,fontsize='16')
fig.sca(_ax1)
xg.plot_security_k(_ax1, _his, _beginindex, 60)
#成交量
fig.sca(ax1)
xg.plot_volume_overlay(ax1, _his, _beginindex)
ax1.yaxis.set_visible(False)
plt.show()