def load_macro_data_wind(self,
macro_code="M0000545",
beg_date="19900101",
end_date=datetime.today().strftime("%Y%m%d")):
""" 下载宏观数据 """
from WindPy import w
w.start()
beg_date = Date().change_to_str(beg_date)
end_date = Date().change_to_str(end_date)
# 下载数据
##############################################################################
data = w.edb(macro_code, beg_date, end_date, "Fill=Previous")
new_data = pd.DataFrame(data.Data,
columns=data.Times,
index=data.Codes).T
new_data = new_data.dropna()
new_data.index = new_data.index.map(lambda x: x.strftime('%Y%m%d'))
print(" Loading Macro Data %s From %s To %s " %
(macro_code, beg_date, end_date))
out_file = os.path.join(self.data_path, macro_code + '.csv')
if os.path.exists(out_file):
data = pd.read_csv(out_file, encoding='gbk', index_col=[0])
data.index = data.index.map(str)
data = FactorOperate().pandas_add_row(data, new_data)
else:
print(" File No Exist ", macro_code)
data = new_data
data = data.dropna(how='all')
data.to_csv(out_file)
def load_index_factor(self,
index_code="000300.SH",
beg_date=None,
end_date=datetime.today().strftime("%Y%m%d"),
primary=False):
""" 下载一个指数 最近的Factor """
from WindPy import w
w.start()
out_file = os.path.join(self.data_data_factor, index_code + '.csv')
if beg_date is None and os.path.exists(out_file):
beg_date = Date().get_trade_date_offset(end_date, -20)
if beg_date is None and not os.path.exists(out_file):
try:
base_data = w.wsd(index_code, "basedate")
beg_date = base_data.Data[0][0].strftime("%Y%m%d")
except Exception as e:
beg_date = '19991231'
beg_date = Date().change_to_str(beg_date)
end_date = Date().change_to_str(end_date)
print(beg_date, end_date, index_code, primary)
# 下载数据
##############################################################################
if primary:
index_data = w.wsd(index_code, "close,pe_ttm,pb_lf", beg_date,
end_date, "Fill=Previous")
else:
index_data = w.wsd(index_code, "close", beg_date, end_date,
"Fill=Previous")
new_data = pd.DataFrame(index_data.Data,
index=index_data.Fields,
columns=index_data.Times).T
new_data.index = new_data.index.map(lambda x: x.strftime('%Y%m%d'))
print(new_data)
try:
new_data['PCT'] = new_data['CLOSE'].pct_change()
print(" Loading Index Factor ", index_code)
if os.path.exists(out_file):
data = pd.read_csv(out_file, encoding='gbk', index_col=[0])
data.index = data.index.map(str)
data = FactorOperate().pandas_add_row(data, new_data)
else:
print(" File No Exist ", index_code)
data = new_data
data = data.dropna(how='all')
data.to_csv(out_file)
except Exception as e:
print(e)
print(" Loading Index Factor Error", index_code)
def load_fund_factor(self, factor_name, beg_date, end_date):
""" 财汇数据库下载基金因子数据（增量更新） """
beg_date = Date().change_to_str(beg_date)
end_date = Date().change_to_str(end_date)
print("Loading Fund Factor %s From %s To %s" %
(factor_name, beg_date, end_date))
new_data = FinDb().load_raw_data_filter_period(factor_name, beg_date,
end_date)
fund_info_data = FundStatic().get_findb_fund_info()
table_name, field_en, filter_field, field_ch, val_name = FinDb(
).get_load_findb_param(factor_name)
new_data = pd.merge(new_data, fund_info_data, on="证券内码", how='inner')
new_data = pd.DataFrame(
new_data[val_name].values,
index=[list(new_data['基金代码'].values),
list(new_data['日期'].values)])
new_data = new_data.sort_index()
new_data = new_data[~new_data.index.duplicated()]
new_data = new_data.unstack()
new_data.columns = new_data.columns.droplevel(level=0)
new_data = new_data.T
new_data = new_data.dropna(how='all')
new_data.index = new_data.index.map(str)
out_file = os.path.join(self.data_path_factor, factor_name + '.csv')
if os.path.exists(out_file):
data = pd.read_csv(out_file, encoding='gbk', index_col=[0])
data.index = data.index.map(str)
data = FactorOperate().pandas_add_row(data, new_data)
else:
print(" File No Exist ", factor_name)
data = new_data
data = data.dropna(how='all')
data.to_csv(out_file)