def parse_sw_history2(begin_date='2014-03-12', end_date=None, code='801150'):
if end_date is None:
now = arrow.now()
end_date = str(now.date())
condition = 'swindexcode=\'{}\' and BargainDate>=\'{}\' and BargainDate<=\'{}\' and type=\'Day\''
where = condition.format(code, begin_date, end_date)
all_data = []
for index in range(1, 1000):
payload = {'tablename':'V_Report',
'key': 'id',
'p': index,
'where': where,
'orderby': 'swindexcode asc,BargainDate_1',
'fieldlist': 'SwIndexCode,SwIndexName,BargainDate,CloseIndex,BargainAmount,Markup,'
'TurnoverRate,PE,PB,MeanPrice,BargainSumRate,DP',
'pagecount': 1,
'timed': 1456667319778
}
url = 'http://www.swsindex.com/handler.aspx'
res = requests.post(url, data=payload)
data = res.text.replace('\'', '\"')
print data
result = json.loads(data)
data_list = result.get('root')
print 'url****'+url
print len(data_list)
if len(data_list) == 0:
break
else:
all_data.extend(data_list)
df = DataFrame(all_data)
print df
print df.info()
print df.describe()
# print df['PE']
# print df[df['BargainDate'] == '2015-10-16 0:00:00']
# clean data with empty PE or PB
df = df[df['PE'] != '']
df = df[df['PB'] != '']
print df
df[['PE', 'PB']] = df[['PE', 'PB']].astype(float)
print '*'*20
print len(df)
df_sort_pe = df.sort(columns='PE', ascending=True)
print df_sort_pe
df_sort_pb = df.sort(columns='PB', ascending=True)
print df_sort_pb
print 'PE mean:{}'.format(df['PE'].mean())
print 'PB mean:{}'.format(df['PB'].mean())
print 'PB<1:{}'.format(df[df.PB < 1])
return df
def parse_sw_history(begin_date='2014-03-12', end_date=None, codes=None):
if end_date is None:
now = arrow.now()
end_date = str(now.date())
if codes is None:
codes = ('801010', '801020', '801030', '801040', '801050', '801060', '801070', '801080', '801090',
'801100', '801110', '801120', '801130', '801140', '801150', '801160', '801170', '801180', '801190',
'801200', '801210', '801220', '801230',
'801710', '801720', '801730', '801740', '801750', '801760', '801770', '801780', '801790',
'801880', '801890')
condition = 'swindexcode in {} and BargainDate>=\'{}\' and BargainDate<=\'{}\''
where = condition.format(codes, begin_date, end_date)
print where
all_data = []
for index in range(1, 1000):
payload = {'tablename':'swindexhistory',
'key': 'id',
'p': index,
'where': where,
'orderby': 'swindexcode asc,BargainDate_1',
'fieldlist': 'SwIndexCode,SwIndexName,BargainDate,CloseIndex,BargainAmount,Markup,'
'TurnoverRate,PE,PB,MeanPrice,BargainSumRate,DP',
'pagecount': 28,
'timed': 1453385628267
}
url = 'http://www.swsindex.com/handler.aspx'
res = requests.post(url, data=payload)
data = res.text.replace('\'', '\"')
result = json.loads(data)
data_list = result.get('root')
print 'url****'+url
print len(data_list)
if len(data_list) == 0:
break
else:
all_data.extend(data_list)
df = DataFrame(all_data)
df[['PE', 'PB']] = df[['PE', 'PB']].astype(float)
# df['PE'] = df['PE'].astype(float)
# df['PB'] = df['PB'].astype(float)
print '*'*20
print len(df)
print df
df = df.sort(columns='PE', ascending=True)
print df
df = df.sort(columns='PB', ascending=True)
print df
print 'PE mean:{}'.format(df['PE'].mean())
print 'PB mean:{}'.format(df['PB'].mean())
print 'PB<1:{}'.format(df[df.PB < 1])
return df
def parse_sw_history(begin_date='2014-03-12', end_date=None, codes=None):
if end_date is None:
now = arrow.now()
end_date = str(now.date())
if codes is None:
codes = ('801010', '801020', '801030', '801040', '801050', '801060', '801070', '801080', '801090',
'801100', '801110', '801120', '801130', '801140', '801150', '801160', '801170', '801180', '801190',
'801200', '801210', '801220', '801230',
'801710', '801720', '801730', '801740', '801750', '801760', '801770', '801780', '801790',
'801880', '801890')
condition = 'swindexcode in {} and BargainDate>=\'{}\' and BargainDate<=\'{}\''
where = condition.format(codes, begin_date, end_date)
# print where
all_data = []
for index in range(1, 1000):
payload = {'tablename':'swindexhistory',
'key': 'id',
'p': index,
'where': where,
'orderby': 'swindexcode asc,BargainDate_1',
'fieldlist': 'SwIndexCode,SwIndexName,BargainDate,CloseIndex,BargainAmount,Markup,'
'TurnoverRate,PE,PB,MeanPrice,BargainSumRate,DP',
'pagecount': 28,
'timed': 1453385628267
}
url = 'http://www.swsindex.com/handler.aspx'
res = requests.post(url, data=payload)
data = res.text.replace('\'', '\"')
result = json.loads(data)
data_list = result.get('root')
# print 'url****'+url
# print len(data_list)
if len(data_list) == 0:
break
else:
all_data.extend(data_list)
df = DataFrame(all_data)
df[['PE', 'PB']] = df[['PE', 'PB']].astype(float)
# df['PE'] = df['PE'].astype(float)
# df['PB'] = df['PB'].astype(float)
# print '*'*20
# print len(df)
# print df
df = df.sort(columns='PE', ascending=True)
# print df
df = df.sort(columns='PB', ascending=True)
# print df
# print 'PE mean:{}'.format(df['PE'].mean())
# print 'PB mean:{}'.format(df['PB'].mean())
# print 'PB<1:{}'.format(df[df.PB < 1])
return df
def ah_premium_index(samples=[('600036', '03968'), ('600196', '02196'), ('601111', '00753')]):
samples = [('600585', '00914'), ('601318', '02318'), ('000002', '02202'),
('600036', '03968'), ('600600', '00168'), ('600196', '02196'),
('600030', '06030'), ('600028', '00386'), ('601601', '02601'),
('601628', '02628'), ('000063', '00763'), ('601398', '01398'),
('601939', '00939'), ('601288', '01288'), ('600837', '06837'),
('601607', '02607'), ('600011', '00902'), ('002202', '02208'),
('601988', '03988'), ('601818', '06818'), ('601336', '01336'),
('600027', '01071'), ('601088', '01088'), ('601328', '03328'),
('600016', '01988'), ('601998', '00998'), ('601186', '01186'),
('600332', '00874'), ('601766', '01766'), ('002594', '01211'),
('601857', '00857'), ('000039', '02039'), ('600362', '00358'),
('600012', '00995'), ('601633', '02333'), ('601800', '01800'),
('601333', '00525'), ('601111', '00753'), ('600875', '01072'),
('601390', '00390'), ('601898', '01898'), ('601899', '02899'),
('000898', '00347'), ('000157', '01157'), ('600685', '00317'),
('601992', '02009'), ('601600', '02600'), ('601991', '00991'),
('600115', '00670'), ('601808', '02883'), ('600871', '01033'),
('601727', '02727'), ('600188', '01171'), ('601238', '02238'),
('601919', '01919'), ('601866', '02866'), ('601618', '01618'),
('600026', '01138'), ('601880', '02880'), ('600874', '01065'),
('600660', '03606'), ('600377', '00177'), ('000776', '01776'),
('601688', '06886'), ('000338', '02338'), ('600029', '01055'),
('603993', '03993'), ('601005', '01053'), ('600688', '00338'),
('600548', '00548'), ('002672', '00895'), ('000513', '01513'),
('000488', '01812'), ('601107', '00107'), ('601588', '00588'),
('600808', '00323'), ('000921', '00921'), ('600775', '00553'),
('600860', '00187'), ('000756', '00719'), ('601038', '00038'),
('600806', '00300'), ('002490', '00568'), ('002703', '01057'),
('600876', '01108'), ('601717', '00564'), ('000585', '00042')]
a_list = []
h_list = []
price_a_list = []
price_h_list = []
ratio_list = []
hk_to_rmb = float(rmb_exchange_rate()[0])/100
for sample in samples:
ratio = ah_ratio(hk_to_rmb, sample)
if ratio:
a_list.append(sample[0])
h_list.append(sample[1])
price_a_list.append(ratio.get('price_a'))
price_h_list.append(ratio.get('price_h'))
ratio_list.append(ratio.get('ratio'))
df_dict = {'A': a_list, 'Price_A': price_a_list, 'H': h_list, 'Price_H': price_h_list, 'ratio': ratio_list}
print df_dict
df = DataFrame(df_dict)
# print df
df = df.sort(columns='ratio', ascending=True)
print df
# ah_index = np.mean(ratio_list)
ah_index = df['ratio'].mean()
print 'ah_index:{}'.format(ah_index)
print 'discount stock:{}'.format(df[df.ratio < 1])
return AhIndex(ah_index)
def ah_premium_index(samples=[('600036', '03968'), ('600196', '02196'), ('601111', '00753')]):
samples = [('600585', '00914'), ('601318', '02318'), ('000002', '02202'),
('600036', '03968'), ('600600', '00168'), ('600196', '02196'),
('600030', '06030'), ('600028', '00386'), ('601601', '02601'),
('601628', '02628'), ('000063', '00763'), ('601398', '01398'),
('601939', '00939'), ('601288', '01288'), ('600837', '06837'),
('601607', '02607'), ('600011', '00902'), ('002202', '02208'),
('601988', '03988'), ('601818', '06818'), ('601336', '01336'),
('600027', '01071'), ('601088', '01088'), ('601328', '03328'),
('600016', '01988'), ('601998', '00998'), ('601186', '01186'),
('600332', '00874'), ('601766', '01766'), ('002594', '01211'),
('601857', '00857'), ('000039', '02039'), ('600362', '00358'),
('600012', '00995'), ('601633', '02333'), ('601800', '01800'),
('601333', '00525'), ('601111', '00753'), ('600875', '01072'),
('601390', '00390'), ('601898', '01898'), ('601899', '02899'),
('000898', '00347'), ('000157', '01157'), ('600685', '00317'),
('601992', '02009'), ('601600', '02600'), ('601991', '00991'),
('600115', '00670'), ('601808', '02883'), ('600871', '01033'),
('601727', '02727'), ('600188', '01171'), ('601238', '02238'),
('601919', '01919'), ('601866', '02866'), ('601618', '01618'),
('600026', '01138'), ('601880', '02880'), ('600874', '01065'),
('600660', '03606'), ('600377', '00177'), ('000776', '01776'),
('601688', '06886'), ('000338', '02338'), ('600029', '01055'),
('603993', '03993'), ('601005', '01053'), ('600688', '00338'),
('600548', '00548'), ('002672', '00895'), ('000513', '01513'),
('000488', '01812'), ('601107', '00107'), ('601588', '00588'),
('600808', '00323'), ('000921', '00921'), ('600775', '00553'),
('600860', '00187'), ('000756', '00719'), ('601038', '00038'),
('600806', '00300'), ('002490', '00568'), ('002703', '01057'),
('600876', '01108'), ('601717', '00564'), ('000585', '00042')]
a_list = []
h_list = []
price_a_list = []
price_h_list = []
ratio_list = []
hk_to_rmb = float(rmb_exchange_rate()[0])/100
for sample in samples:
ratio = ah_ratio(hk_to_rmb, sample)
if ratio:
a_list.append(sample[0])
h_list.append(sample[1])
price_a_list.append(ratio.get('price_a'))
price_h_list.append(ratio.get('price_h'))
ratio_list.append(ratio.get('ratio'))
df_dict = {'A': a_list, 'Price_A': price_a_list, 'H': h_list, 'Price_H': price_h_list, 'ratio': ratio_list}
# print df_dict
df = DataFrame(df_dict)
# print df
df = df.sort(columns='ratio', ascending=True)
# print df
# ah_index = np.mean(ratio_list)
ah_index = df['ratio'].mean()
# print 'ah_index:{}'.format(ah_index)
# print 'discount stock:{}'.format(df[df.ratio < 1])
return AhIndex(ah_index)
def parse_sw_history2(begin_date='2014-03-12', end_date=None, code='801150'):
if end_date is None:
now = arrow.now()
end_date = str(now.date())
condition = 'swindexcode=\'{}\' and BargainDate>=\'{}\' and BargainDate<=\'{}\' and type=\'Day\''
where = condition.format(code, begin_date, end_date)
all_data = []
for index in range(1, 1000):
payload = {
'tablename':
'V_Report',
'key':
'id',
'p':
index,
'where':
where,
'orderby':
'swindexcode asc,BargainDate_1',
'fieldlist':
'SwIndexCode,SwIndexName,BargainDate,CloseIndex,BargainAmount,Markup,'
'TurnoverRate,PE,PB,MeanPrice,BargainSumRate,DP',
'pagecount':
1,
'timed':
1456667319778
}
url = 'http://www.swsindex.com/handler.aspx'
res = requests.post(url, data=payload)
data = res.text.replace('\'', '\"')
# print data
result = json.loads(data)
data_list = result.get('root')
# print 'url****'+url
# print len(data_list)
if len(data_list) == 0:
break
else:
all_data.extend(data_list)
df = DataFrame(all_data)
# print df
# print df.info()
# print df.describe()
# print df['PE']
# print df[df['BargainDate'] == '2015-10-16 0:00:00']
# clean data with empty PE or PB
df = df[df['PE'] != '']
df = df[df['PB'] != '']
# convert string to datetime(timestamp)
df['BargainDate'] = pd.to_datetime(df['BargainDate'])
# convert string to float
df[['PE', 'PB']] = df[['PE', 'PB']].astype(float)
df_sort_pe = df.sort(columns='PE', ascending=True)
# print df_sort_pe
df_sort_pb = df.sort(columns='PB', ascending=True)
# print df_sort_pb
# print 'PE mean:{}'.format(df['PE'].mean())
# print 'PB mean:{}'.format(df['PB'].mean())
# print 'PB<1:{}'.format(df[df.PB < 1])
return df
