def get_edb(idx_universe, start_date, end_date, names=None, **options):
'''
获取经济数据。
Parameters
------------
idx_universe
经济指标代码
start_date
'20160101'
end_date
'20170101'
names
list of str,列别名,默认为None
options
其他参数
Returns
--------
DataFrame
Notes
------
names若不为None,则必须与idx_universe等长对应
'''
assert len(names) == len(idx_universe)
options = dict_2_str(options)
start_date = date_format_convert(start_date)
end_date = date_format_convert(end_date)
idx_universe = ','.join(idx_universe)
edb = w.edb(idx_universe, start_date, end_date, options)
df = pd.DataFrame(edb.Data, columns=edb.Times, index=names).T
return df
def get_tdays(start_date, end_date, **options):
'''
获取交易日历序列。
Parameters
---------------
start_date
'20101001'
end_date
'20171021'
options
其他参数
Returns
--------
Series[]-=
-98
Datetime64,ASC
'''
options = dict_2_str(options)
start_date = date_format_convert(start_date)
end_date = date_format_convert(end_date)
t_days = w.tdays(start_date, end_date, options)
t_days = pd.Series(t_days.Data[0])
return t_days
def get_wsd(universe,
factors,
start_date,
end_date,
names=None,
if_convert=False,
**options):
'''
获取万德日期序列数据。
Parameters
----------
universe
list ['600340','000001']
factors
'pe_ttm,pb_mrq'
start_date
'20171011'
end_date
'20171021'
if_convert
是否将universe转换成wind代码,默认为False,仅支持沪深股票
names
list of str,列别名,默认为None,仅对单标的多因素
options
其他参数
Returns
--------
DataFrame
Notes
----------
universe与factors最多有一个是多维。
'''
options = dict_2_str(options)
start_date = date_format_convert(start_date)
end_date = date_format_convert(end_date)
if if_convert:
universe_wind = code_2_wind_symbol(universe)
universe_wind = ','.join(universe_wind)
else:
universe_wind = ','.join(universe)
data = w.wsd(universe_wind, factors, start_date, end_date, options)
if len(universe) == 1:
if names is not None:
df = pd.DataFrame(data.Data, columns=data.Times, index=names).T
else:
df = pd.DataFrame(data.Data, columns=data.Times,
index=data.Fields).T
else:
df = pd.DataFrame(data.Data, columns=data.Times, index=data.Codes).T
return df
def get_tdaysoffset(num, date, **options):
'''
获取日期端点数据。
Parameters
-----------
num
int,正为面向未来,负为面向过去
date
str,'2018-05-10'
Returns
-------
datetime
'''
options = dict_2_str(options)
date = w.tdaysoffset(num, date, options)
return date.Data[0][0]
def get_wsi(universe,
factors,
start_datetime,
end_datetime,
names=None,
**options):
'''
获取万德分钟序列数据。
Parameters
----------
universe
list ['600340.SH','000001.SZ']
factors
'close,volume'
start_datetime
'2017-10-11 09:00:00'
end_date
'2017-10-21 15:00:00'
names
list of str,列别名,默认为None,仅对单标的多因素
options
其他参数
Returns
--------
DataFrame
Notes
----------
universe与factors最多有一个是多维。
'''
options = dict_2_str(options)
universe_wind = ','.join(universe)
data = w.wsi(universe_wind, factors, start_datetime, end_datetime, options)
if names is not None:
df = pd.DataFrame(data.Data, columns=data.Times, index=names).T
else:
df = pd.DataFrame(data.Data, columns=data.Times, index=data.Fields).T
return df
def get_wset(set_name, **options):
'''
获取数据集数据。
Parameters
-----------
set_name
集合名称
options
选项
Returns
----------
DataFrame
'''
options = dict_2_str(options)
data = w.wset(set_name, options)
data = pd.DataFrame(data.Data, index=data.Fields).T
return data
def get_wss(universe, factors, if_convert=False, names=None, **options):
'''
获取万德多维数据。
Parameters
----------
universe
list ['600340','000001']
factors
'pe_ttm,pb_mrq'
if_convert
是否将universe转换成wind代码,默认为False,仅支持沪深股票
names
list of str,列别名,默认为None
options
其他参数,如tradeDate = '20171009'
Returns
--------
DataFrame
'''
options = dict_2_str(options)
if names is not None:
assert len(names) == len(factors.split(','))
if if_convert:
universe_wind = code_2_wind_symbol(universe)
universe_wind = ','.join(universe_wind)
else:
universe_wind = ','.join(universe)
data = w.wss(universe_wind, factors, options)
if names is not None:
df = pd.DataFrame(data.Data, index=names, columns=universe).T
else:
df = pd.DataFrame(data.Data, index=data.Fields, columns=universe).T
return df