def to_hfq(self):
if self.if_fq is 'bfq':
return self.new(pd.concat(list(map(lambda x: QA_data_stock_to_fq(
self.data[self.data['code'] == x], 'hfq'), self.code))), self.type, 'hfq')
else:
QA_util_log_info(
'none support type for qfq Current type is: %s' % self.if_fq)
return self
def to_hfq(self):
if self.if_fq is 'bfq':
data = QA_DataStruct_Stock_day(pd.concat(list(map(lambda x: QA_data_stock_to_fq(
self.data[self.data['code'] == x], '01'), self.code))))
data.if_fq = 'hfq'
return data
else:
QA_util_log_info(
'none support type for qfq Current type is: %s' % self.if_fq)
return self
def to_qfq(self):
if self.if_fq is 'bfq':
data = QA_DataStruct_Stock_min(pd.concat(list(map(lambda x: QA_data_stock_to_fq(
self.data[self.data['code'] == x]), self.code))).set_index(['datetime', 'code'], drop=False))
data.if_fq = 'qfq'
return data
else:
QA_util_log_info(
'none support type for qfq Current type is:%s' % self.if_fq)
return self
def to_qfq(self):
if self.if_fq is 'bfq':
if len(self.code) < 20:
return self.new(pd.concat(list(map(
lambda x: QA_data_stock_to_fq(self.data[self.data['code'] == x]), self.code))), self.type, 'qfq')
else:
return self.new(
self.data.groupby('code').apply(QA_data_stock_to_fq), self.type, 'qfq')
else:
QA_util_log_info(
'none support type for qfq Current type is: %s' % self.if_fq)
return self
def to_qfq(self):
if self.if_fq is 'bfq':
if len(self.code) < 20:
data = QA_DataStruct_Stock_day(pd.concat(list(map(
lambda x: QA_data_stock_to_fq(self.data[self.data['code'] == x]), self.code))))
data.if_fq = 'qfq'
return data
else:
data = QA_DataStruct_Stock_day(
self.data.groupby('code').apply(QA_data_stock_to_fq))
data.if_fq = 'qfq'
return data
else:
QA_util_log_info(
'none support type for qfq Current type is: %s' % self.if_fq)
return self