def test_remote_data_service_industry_df():
from jaqs.data.dataservice import Calendar
cal = Calendar()
ds = RemoteDataService()
ds.init_from_config()
arr = ds.get_index_comp(index='000300.SH',
start_date=20130101,
end_date=20170505)
symbol_arr = ','.join(arr)
sec = '000008.SZ'
type_ = 'ZZ'
df_raw = ds.get_industry_raw(symbol=sec, type_=type_)
df = ds.get_industry_daily(symbol=symbol_arr,
start_date=df_raw['in_date'].min(),
end_date=20170505,
type_=type_,
level=1)
for idx, row in df_raw.iterrows():
in_date = row['in_date']
value = row['industry1_code']
if in_date in df.index:
assert df.loc[in_date, sec] == value
else:
idx = cal.get_next_trade_date(in_date)
assert df.loc[idx, sec] == value
def test_remote_data_service_industry():
from jaqs.data.align import align
import pandas as pd
ds = RemoteDataService()
arr = ds.get_index_comp(index='000300.SH', start_date=20130101, end_date=20170505)
df = ds.get_industry_raw(symbol=','.join(arr), type_='ZZ')
df = df.astype(dtype={'in_date': int})
# df_ann = df.loc[:, ['in_date', 'symbol']]
# df_ann = df_ann.set_index(['symbol', 'in_date'])
# df_ann = df_ann.unstack(level='symbol')
from jaqs.data.dataview import DataView
dic_sec = DataView._group_df_to_dict(df, by='symbol')
dic_sec = {sec: df.reset_index() for sec, df in dic_sec.viewitems()}
df_ann = pd.concat([df.loc[:, 'in_date'].rename(sec) for sec, df in dic_sec.viewitems()], axis=1)
df_value = pd.concat([df.loc[:, 'industry1_code'].rename(sec) for sec, df in dic_sec.viewitems()], axis=1)
dates_arr = ds.get_trade_date(20140101, 20170505)
res = align(df_value, df_ann, dates_arr)
# df_ann = df.pivot(index='in_date', columns='symbol', values='in_date')
# df_value = df.pivot(index=None, columns='symbol', values='industry1_code')
def align_single_df(df_one_sec):
df_value = df_one_sec.loc[:, ['industry1_code']]
df_ann = df_one_sec.loc[:, ['in_date']]
res = align(df_value, df_ann, dates_arr)
return res
# res_list = [align_single_df(df) for sec, df in dic_sec.viewitems()]
res_list = [align_single_df(df) for sec, df in dic_sec.items()[:10]]
res = pd.concat(res_list, axis=1)