plt.axvline(k - 0.5, alpha=0.6)
plt.title('Northbound Cash Flow TOP' + str(k) + ' ' + date, size=title_size)
plt.text((k - 4) / 2,
text_loc,
'Top Inflow',
size=title_size,
alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text((k - 4) / 2 + k,
text_loc,
'Top Outflow',
size=title_size,
alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
ax.set_xticklabels(northbound_rank.index,
rotation=90,
fontsize=txt_size,
color='red')
plt.savefig(sub_file_path + '\\%s' % 'Northbound CF TOP')
today = datetime.today().date().strftime('%Y-%m-%d')
attachment_list = [
sub_file_path + '\\Northbound CF TOP.png',
sub_file_path + '\\北向净流出T20.png', sub_file_path + '\\北向净流入TOP20.png'
]
send_email('%s:北向资金流入流出TOP个股' % today,
'流入流出TOP个股',
images=attachment_list,
receivers=NORTH_GROUP)
fig = plt.figure(figsize=(20, 10))
ax = plt.subplot(211)
hk_to_all.sum(axis=1).plot(kind='bar', legend=False, ax=ax)
ax2 = ax.twinx()
ax2.set_ylim(ax.get_ylim())
plt.grid(False)
ax.set_title(f'Northbound Cash Flow, {hk_to_all.index[-1]:%Y-%m-%d}')
ax3 = plt.subplot(212)
hk_to_all.plot(kind='bar', stacked=True, legend=True, ax=ax3, sharex=True)
ax4 = ax3.twinx()
ax4.set_ylim(ax3.get_ylim())
plt.grid(False)
ax3.set_title(f'SH vs. SZ')
plt.savefig(sub_file_path + '\\%s.png' % f'SHvsSZ')
today = datetime.today().date().strftime('%Y-%m-%d')
attachment_list = [
sub_file_path + '\\NorthboundCashFlow1-10_%s.png' % date_end,
sub_file_path + '\\NorthboundCashFlow11-20_%s.png' % date_end,
sub_file_path + '\\SHNorthboundCashFlow1-10_%s.png' % date_end,
sub_file_path + '\\SHNorthboundCashFlow11-20_%s.png' % date_end,
sub_file_path + '\\SZNorthboundCashFlow1-10_%s.png' % date_end,
sub_file_path + '\\SZNorthboundCashFlow11-20_%s.png' % date_end,
sub_file_path + '\\SHvsSZ.png'
]
send_email('%s:机构北向资金流动对比（按市场）' % today,
'机构北向资金流动对比（按市场）',
images=attachment_list,
receivers=NORTH_GROUP)
plt.title('Southbound Cash Flow TOP' + str(k) + ' ' + date, size=title_size)
plt.text((k - 4) / 2,
text_loc,
'Top ' + str(k) + ' Inflow: ' +
str(southbound_rank['CF'][:k].sum().round(2)) + '亿元\n\n' +
'Total Inflow: ' +
str(southbound_cf.query('CF>0')['CF'].sum().round(2)) + '亿元',
size=txt_size + 5,
alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text((k - 4) / 2 + k,
text_loc,
'Top ' + str(k) + ' Outflow: ' +
str(southbound_rank['CF'][-k:].sum().round(2)) + '亿元\n\n' +
'Total Outflow: ' +
str(southbound_cf.query('CF<0')['CF'].sum().round(2)) + '亿元',
size=txt_size + 5,
alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.savefig(sub_file_path +
'\\南向资金净流入净流出个股_%s' % date_end.strftime('%Y-%m-%d'))
today = datetime.today().date().strftime('%Y-%m-%d')
attachment_list = [sub_file_path + '\\南向资金净流入净流出个股_%s.png' % date_end]
send_email('%s:南向资金净流入净流出个股' % today,
'南向资金净流入净流出个股',
images=attachment_list,
receivers=NORTH_GROUP)
plt.axvline(9.5, alpha=0.6)
plt.axvline(10.5, alpha=0.6)
plt.axvline(16.5, alpha=0.6)
plt.axvline(20.5, alpha=0.6)
plt.axvline(23.5, alpha=0.6)
plt.axvline(28.5, alpha=0.6)
plt.text(1, text_loc, "周期\n" + str(cash_flow_ind.at['周期', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(6.5, text_loc, "制造\n" + str(cash_flow_ind.at['制造', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(9.6, text_loc, "医药\n" + str(cash_flow_ind.at['医药', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(13, text_loc, "消费\n" + str(cash_flow_ind.at['消费', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(18, text_loc, "科技\n" + str(cash_flow_ind.at['科技', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(21, text_loc, "金融\n" + str(cash_flow_ind.at['金融', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(25, text_loc, "基地\n" + str(cash_flow_ind.at['基地', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.text(29, text_loc, "综合\n" + str(cash_flow_ind.at['综合', 'cash_flow'].round(2)), size=txt_size, alpha=2,
bbox=dict(facecolor='g', edgecolor='blue', alpha=0.35))
plt.savefig(sub_file_path+'\\%s' % "中信一级行业涨跌幅与北向资金净流入对比")
today=datetime.today().date().strftime('%Y-%m-%d')
attachment_list=[sub_file_path+"\\中信一级行业涨跌幅与北向资金净流入对比.png"]
send_email('%s:中信一级行业分类北向资金数据' % today,'中信一级行业分类北向资金数据',
images=attachment_list,
receivers=NORTH_GROUP)
attachment_list8 = []
for file1, file2, file3, file4 in zip(attachment_list3, attachment_list4,
attachment_list5, attachment_list6):
attachment_list7.extend([file1, file2])
attachment_list8.extend([file3, file4])
attachment_list1 = [x + '.png' for x in attachment_list1]
attachment_list2 = [x + '.png' for x in attachment_list2]
attachment_list3 = [x + '.png' for x in attachment_list3]
attachment_list4 = [x + '.png' for x in attachment_list4]
attachment_list7 = [x + '.png' for x in attachment_list7]
attachment_list8 = [x + '.png' for x in attachment_list8]
send_email('%s:北向资金净流入TOP3机构资金去向(个股)' % today,
'北向资金净流入TOP机构资金去向(个股)',
images=attachment_list7,
receivers=NORTH_GROUP)
send_email('%s:北向资金净流出TOP3机构资金去向(个股)' % today,
'北向资金净流出TOP机构资金去向(个股)',
images=attachment_list8,
receivers=NORTH_GROUP)
send_email('%s:北向资金净流入TOP3机构资金去向(行业)' % today,
'北向资金净流入TOP机构资金去向(行业)',
images=attachment_list1,
receivers=NORTH_GROUP)
send_email('%s:北向资金净流出TOP3机构资金去向(行业)' % today,
'北向资金净流出TOP机构资金去向(行业)',
images=attachment_list2,
stacked=True,
legend=False,
ax=ax,
sharex=True,
width=0.3)
plt.legend(loc='lower right', fontsize=14)
ax2 = ax.twinx()
summary.iloc[:, -1].plot(kind='bar',
legend=False,
ax=ax2,
edgecolor='r',
linewidth=3,
facecolor='none')
ylim = (b_limit, t_limit)
ax.set_ylim(ylim)
ax2.set_ylim(ylim)
ax2.axis(False)
ax2.grid(False)
plt.gcf().autofmt_xdate()
plt.title(act_top.index[j] + ' ' + act_top.iloc[j, 2] + ' (' +
'%.2f%%' % act_top.iloc[j, -1].round(2) + ')',
size=25)
fig.suptitle(date + ' 活跃个股TOP10（按市场）', fontsize=50)
plt.savefig(sub_file_path + '\\%s' % '活跃个股TOP10(按市场)')
today = datetime.today().date().strftime('%Y-%m-%d')
attachment_list = sub_file_path + '\\活跃个股TOP10(按市场).png'
send_email('%s:北向资金成交活跃个股TOP10' % today,
'成交活跃个股TOP10',
images=attachment_list,
receivers=NORTH_GROUP)