核心功能与使用示例

读取因子数据的核心模块

concat_nosqls

 concat_nosqls (func)

do_on_dfs_class

 do_on_dfs_class (func)

一个装饰器，使类的方法的参数可以输入为列表或元组，返回值为分别对各个参数执行此函数后依次得到的结果

TokenUnavailableError

 TokenUnavailableError (error_info)

Not enough permissions.

FactorReader

 FactorReader (token:str)

Initialize self. See help(type(self)) for accurate signature.

FactorReader.show_all_factors_information

 FactorReader.show_all_factors_information ()

FactorReader.read_factor

 FactorReader.read_factor (fac_key:str,
                           trade_date:Union[int,str,datetime.datetime]=Non
                           e, start_date:Union[int,str,datetime.datetime]=
                           None,
                           end_date:Union[int,str,datetime.datetime]=None,
                           sql_like:bool=False)

通过表名，读取因子数据

	Type	Default	Details
fac_key	str		表的名称或因子的名称
trade_date	typing.Union[int, str, datetime.datetime]	None	读取单日因子值，形如20230106或’20230106’或’2023-01-13’或pd.Timestamp(‘2023-01-13’)，指定此参数时，start_date和end_date两个参数将失效, by default None
start_date	typing.Union[int, str, datetime.datetime]	None	读取因子值的起始日期，形如20230106或’20230106’或’2023-01-13’或pd.Timestamp(‘2023-01-13’), by default None
end_date	typing.Union[int, str, datetime.datetime]	None	读取因子值的终止日期，形如20230106或’20230106’或’2023-01-13’或pd.Timestamp(‘2023-01-13’), by default None
sql_like	bool	False	返回的数据为形如sql中的长表，包括日期、股票代码、因子值三列, by default False
Returns	DataFrame		因子值，index为每天的日期，columns为股票代码，values为因子值

使用示例

第一步：实例化一个FactorReader对象，输入token

fr=FactorReader(token=token) # 初始化一个FactorReader对象，输入token，连接因子数据库

第二步：查看当前因子数据库中有哪些因子（此步骤可选）

fr.show_all_factors_information() # 展示所有可读取因子的相关信息

	数据键名	因子名称	报告题目	微信链接
0	factor1	适度冒险因子	成交量激增时刻蕴含的alpha信息——多因子选股系列研究之一	https://mp.weixin.qq.com/s/2pObrtp3V0dv50MFGg_fhw
1	factor2	完整潮汐因子	个股成交量的潮汐变化及“潮汐”因子构建——多因子选股系列研究之二	https://mp.weixin.qq.com/s/_2xWXM8iyNzYDYolT9vVsw
2	factor3	勇攀高峰因子	个股波动率的变动及”勇攀高峰“因子构建——多因子选股系列研究之三	https://mp.weixin.qq.com/s/-IxH3n-uR0BwOIbOyzqPrw
3	factor4	球队硬币因子	个股动量效应的识别及“球队硬币”因子构建——多因子选股系列研究之四	https://mp.weixin.qq.com/s/JCv8qziZ_ZfTbBE6l8cKOQ
4	factor5	云开雾散因子	波动率的波动率与投资者模糊性厌恶——多因子选股系列研究之五	https://mp.weixin.qq.com/s/vX4I9SpKRF3_HKQOGhtZcQ
5	factor6	飞蛾扑火因子	个股股价跳跃及其对振幅因子的改进——多因子选股系列研究之六	https://mp.weixin.qq.com/s/V8r1Xbz5J0A9D5J_9GD_IA
6	factor8	草木皆兵因子	显著效应、极端收益扭曲决策权重和“草木皆兵”因子——多因子选股系列研究之八	https://mp.weixin.qq.com/s/hdtzQaCF2h6ZjZd-0HAftQ
7	factor9	水中行舟因子	个股成交额的市场跟随性与“水中行舟”因子——多因子选股系列研究之九	https://mp.weixin.qq.com/s/Zv6XX8ddUvBCtG-4LM1MKQ

第三步：读取因子数据

①读取单日单个因子的数据

fr.read_factor('球队硬币',trade_date=20230106) # 读取球队硬币因子在2023年1月13日的因子数据

正在读取球队硬币因子的数据

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	871970.BJ	871981.BJ	872374.BJ	872808.BJ	872925.BJ	873122.BJ	873169.BJ	873223.BJ	873339.BJ	873527.BJ
name	index
球队硬币因子	2023-01-06	-3.45854	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	0.104238	-1.345124	-1.070172	-3.192394	-1.628848	0.60037	-2.126244	-0.90467	-0.537109	-1.108383

1 rows × 5015 columns

fr.read_factor('factor4',trade_date='20230106') # 读取方正金工多因子系列第4篇的因子在2023年1月13日的因子数据

正在读取球队硬币因子的数据

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	871970.BJ	871981.BJ	872374.BJ	872808.BJ	872925.BJ	873122.BJ	873169.BJ	873223.BJ	873339.BJ	873527.BJ
name	index
球队硬币因子	2023-01-06	-3.45854	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	0.104238	-1.345124	-1.070172	-3.192394	-1.628848	0.60037	-2.126244	-0.90467	-0.537109	-1.108383

1 rows × 5015 columns

②读取多个交易日单个因子的数据

fr.read_factor('球队硬币',start_date='2023-01-01',end_date=pd.Timestamp('20230106')) # 读取球队硬币因子从2023年1月1日至2023年1月13日的因子数据

正在读取球队硬币因子的数据

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	871970.BJ	871981.BJ	872374.BJ	872808.BJ	872925.BJ	873122.BJ	873169.BJ	873223.BJ	873339.BJ	873527.BJ
name	index
球队硬币因子	2023-01-03	-2.358642	-1.345033	1.162492	0.007223	8.697314	1.189680	-1.702174	-1.052431	-0.854015	3.398331	...	-0.103756	-1.137786	-1.021316	-3.253337	-1.775420	2.468078	-1.900470	-1.004885	-0.407954	-0.799920
	2023-01-04	-3.250196	-0.612765	1.104373	-0.604997	8.853588	0.434524	-2.027665	-1.078369	-1.319052	2.476316	...	-0.088794	-1.116035	-1.024373	-3.126951	-1.740175	2.741972	-2.164878	-0.959739	-0.397286	-0.845371
	2023-01-05	-3.612259	-0.353330	0.683165	-0.712644	8.803313	0.304470	-1.978654	-0.557577	-1.869844	2.610491	...	0.010475	-1.115315	-1.121056	-3.268384	-1.753120	1.020633	-2.132997	-0.893447	-0.449713	-0.817057
	2023-01-06	-3.458540	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	0.104238	-1.345124	-1.070172	-3.192394	-1.628848	0.600370	-2.126244	-0.904670	-0.537109	-1.108383

4 rows × 5017 columns

fr.read_factor('factor4',start_date=20230101,end_date=20230106,sql_like=True) # 以sql的形式，读取方正金工多因子系列第4篇的因子从2023年1月1日至2023年1月13日的因子数据

正在读取球队硬币因子的数据

	date	code	球队硬币因子
0	2023-01-03	000001.SZ	-2.358642
1	2023-01-03	000002.SZ	-1.345033
2	2023-01-03	000004.SZ	1.162492
3	2023-01-03	000005.SZ	0.007223
4	2023-01-03	000006.SZ	8.697314
...	...	...	...
20045	2023-01-06	873122.BJ	0.600370
20046	2023-01-06	873169.BJ	-2.126244
20047	2023-01-06	873223.BJ	-0.904670
20048	2023-01-06	873339.BJ	-0.537109
20049	2023-01-06	873527.BJ	-1.108383

20050 rows × 3 columns

③读取多个交易日多个因子的因子数据

fr.read_factor(['球队硬币','云开雾散'],start_date='20230101',end_date='20230106') # 分别读取球队硬币因子和云开雾散因子从2023年1月1日至2023年1月13日的因子数据

正在读取球队硬币因子的数据
正在读取云开雾散因子的数据

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	301398.SZ	600038.SH	600459.SH	600663.SH	600729.SH	603029.SH	688141.SH	688147.SH	688172.SH	688498.SH
name	index
球队硬币因子	2023-01-03	-2.358642	-1.345033	1.162492	0.007223	8.697314	1.189680	-1.702174	-1.052431	-0.854015	3.398331	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-04	-3.250196	-0.612765	1.104373	-0.604997	8.853588	0.434524	-2.027665	-1.078369	-1.319052	2.476316	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-05	-3.612259	-0.353330	0.683165	-0.712644	8.803313	0.304470	-1.978654	-0.557577	-1.869844	2.610491	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-06	-3.458540	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
云开雾散因子	2023-01-03	-0.981326	-0.944349	-0.997003	4.198288	3.824620	-0.305261	-2.440184	1.778184	-1.547923	2.822911	...	2.320428	-0.672918	-0.150167	1.191432	0.075872	10.216414	NaN	NaN	1.769576	NaN
	2023-01-04	-0.874760	-0.565374	-1.418436	-2.256764	3.836005	-0.601352	-1.189656	1.456942	-1.902164	2.427931	...	2.093086	-0.477727	-0.157869	1.731492	-0.314115	10.224871	NaN	NaN	1.559961	1.156921
	2023-01-05	-0.254081	-0.614854	-1.407234	-2.364404	3.869275	-1.362426	-1.225968	1.424493	-1.910795	2.395279	...	2.492977	-0.415604	-0.156190	1.573648	0.032488	9.917723	NaN	NaN	1.374394	1.120350
	2023-01-06	-0.291150	-0.524840	-1.476704	-3.120565	3.906959	-1.295554	-1.253691	-0.280816	0.352601	2.508948	...	2.564407	-0.250353	0.183853	1.403672	-0.088864	10.332152	-0.121816	0.644811	1.282682	0.950078

8 rows × 5033 columns

fr.read_factor(['球队硬币','云开雾散'],start_date='20230101',end_date='20230206')

正在读取球队硬币因子的数据
您读取的数据过长，正在分段读取，请稍候……

100%|██████████| 37/37 [00:28<00:00,  1.28it/s]

读取完成，正在拼接，请稍等
正在读取云开雾散因子的数据
您读取的数据过长，正在分段读取，请稍候……

100%|██████████| 37/37 [00:29<00:00,  1.27it/s]

读取完成，正在拼接，请稍等

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	603029.SH	688525.SH	831195.BJ	838262.BJ	872392.BJ	000045.SZ	002387.SZ	000153.SZ	600038.SH	688506.SH
name	index
球队硬币因子	2023-01-03	-2.358642	-1.345033	1.162492	0.007223	8.697314	1.189680	-1.702174	-1.052431	-0.854015	3.398331	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-04	-3.250196	-0.612765	1.104373	-0.604997	8.853588	0.434524	-2.027665	-1.078369	-1.319052	2.476316	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-05	-3.612259	-0.353330	0.683165	-0.712644	8.803313	0.304470	-1.978654	-0.557577	-1.869844	2.610491	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-06	-3.458540	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-09	-3.354882	-0.170424	0.087265	-1.711030	8.091143	0.268643	-1.913154	-0.324667	-1.089943	1.179651	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-10	-4.085837	-1.136618	0.041872	-1.484979	8.123063	0.195857	-1.755869	-0.714262	-1.289059	1.667330	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-11	-4.299566	-1.225560	0.273944	-1.030241	7.683715	0.762255	-1.444859	-1.031784	-1.868811	1.372701	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-12	-4.378207	-1.189928	0.237218	-0.655933	7.894500	0.988860	-1.450630	-1.049240	-1.932018	0.904318	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-13	-4.479527	-1.476970	0.172361	-0.525152	7.266575	1.433193	-1.330020	-0.899924	-2.360796	0.807718	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-16	-4.171016	-1.219680	-1.174946	-0.475743	6.070169	1.243313	-1.233022	-0.939703	-2.208122	1.029549	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-17	-4.023675	-1.386111	-2.004400	-0.622768	5.288382	1.007523	-1.466045	-0.899911	-1.885433	-0.014407	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-18	-4.353316	-2.071842	-2.029811	-0.676816	5.694441	1.046042	-1.427424	-1.070267	-2.242011	0.541593	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-19	-3.834700	-2.081139	-2.126112	-0.692192	5.532381	0.949091	-1.522382	-1.382040	-2.418350	0.680613	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-20	-3.529300	-2.139061	-1.950409	-0.787610	6.188294	-0.064943	-1.693119	-1.255481	-2.089060	1.099186	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-30	-3.396520	-2.177579	-2.041623	-1.006709	4.699233	0.209981	-1.844951	-1.615751	-2.189002	0.647098	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-01-31	-3.307280	-2.372615	-1.825028	-1.052096	4.660585	-0.146351	-1.843303	-1.585481	-2.769475	-0.353974	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
	2023-02-01	-2.712186	-2.285143	-2.908093	-1.144443	2.583668	-0.328338	-1.688609	-1.630970	-2.642992	-0.415580	...	2.624134	9.190541	2.243016	5.085097	2.930902	NaN	NaN	NaN	NaN	NaN
	2023-02-02	-2.475493	-2.352708	-3.016441	-1.441300	1.523398	-0.080891	-1.691300	-1.736535	-2.545913	-0.217612	...	3.471669	8.035542	2.034675	5.038055	2.787796	4.466066	0.000020	NaN	NaN	NaN
	2023-02-03	-2.276289	-2.365098	-2.835789	-1.496792	3.269992	-0.033889	-1.683524	-1.863987	-2.081520	-0.638868	...	5.042774	7.729171	1.799429	4.820005	2.745846	4.197322	0.103416	0.130123	NaN	NaN
	2023-02-06	-2.457774	-2.504629	-2.637363	-1.612015	3.456960	-0.064467	-1.685374	-1.756911	-2.093174	-0.557864	...	4.689956	7.270080	2.828328	3.404015	1.976494	4.459459	-0.093789	-0.010975	NaN	NaN
云开雾散因子	2023-01-03	-0.981326	-0.944349	-0.997003	4.198288	3.824620	-0.305261	-2.440184	1.778184	-1.547923	2.822911	...	10.216414	NaN	NaN	NaN	NaN	NaN	-0.119242	2.722243	-0.672918	NaN
	2023-01-04	-0.874760	-0.565374	-1.418436	-2.256764	3.836005	-0.601352	-1.189656	1.456942	-1.902164	2.427931	...	10.224871	NaN	NaN	NaN	NaN	NaN	-0.176335	NaN	-0.477727	NaN
	2023-01-05	-0.254081	-0.614854	-1.407234	-2.364404	3.869275	-1.362426	-1.225968	1.424493	-1.910795	2.395279	...	9.917723	NaN	NaN	NaN	NaN	NaN	1.390256	NaN	-0.415604	NaN
	2023-01-06	-0.291150	-0.524840	-1.476704	-3.120565	3.906959	-1.295554	-1.253691	-0.280816	0.352601	2.508948	...	10.332152	NaN	NaN	NaN	NaN	NaN	1.369488	NaN	-0.250353	NaN
	2023-01-09	-0.311834	-0.652490	-1.435259	-3.156991	3.906213	-1.317670	-1.064004	-0.284044	0.241210	2.511567	...	10.451378	NaN	NaN	NaN	NaN	NaN	1.790611	NaN	-0.129676	NaN
	2023-01-10	-0.252993	-0.673770	-1.452988	-3.094026	4.145813	-1.365568	-0.990502	0.061734	-0.068599	2.412575	...	9.994998	NaN	NaN	NaN	NaN	NaN	1.753357	NaN	1.476060	NaN
	2023-01-11	-0.108614	-0.409360	-1.538049	-3.050843	4.022810	-1.322641	-0.947558	-0.022587	-0.226062	1.874980	...	9.835279	NaN	NaN	NaN	NaN	NaN	2.050787	NaN	1.580048	NaN
	2023-01-12	-0.019939	-0.348093	-1.517629	-3.235680	4.079903	-1.376875	-0.880969	0.259599	-0.196476	1.914316	...	9.753503	NaN	NaN	NaN	NaN	NaN	3.056719	NaN	1.593361	NaN
	2023-01-13	0.004401	-0.231196	-1.393393	-3.245165	3.799570	-1.262185	-0.851256	-0.057122	-0.185930	2.013694	...	10.744896	2.872292	NaN	NaN	NaN	NaN	3.320740	NaN	1.514023	NaN
	2023-01-16	-0.095033	-0.481757	-1.352985	-3.607232	3.402758	-1.354385	-0.873112	-0.010235	-0.363502	1.528507	...	10.615026	2.599090	NaN	NaN	NaN	NaN	3.364177	NaN	0.875702	NaN
	2023-01-17	0.024778	-0.312762	-1.256656	-3.683347	3.316168	-0.715599	-0.884222	-0.092405	-0.360934	0.865153	...	9.666980	3.535676	NaN	NaN	NaN	1.102298	2.930146	NaN	0.968285	NaN
	2023-01-18	-0.026242	-0.403705	-0.844195	-4.013815	3.142178	-0.796957	-0.984815	-0.125247	-0.493555	0.820175	...	9.768873	14.707472	NaN	NaN	NaN	0.964833	2.595237	-0.017674	0.924300	NaN
	2023-01-19	-0.089630	-0.456148	-0.838379	-4.044224	3.142638	-0.736692	-1.018868	-0.156723	-0.563879	1.005141	...	9.555741	13.743744	NaN	NaN	NaN	2.542283	2.252805	-0.177023	0.931085	1.175814
	2023-01-20	-0.122600	-0.368921	-0.858872	-4.358661	2.865788	-0.362223	-1.177539	-0.086074	-0.468621	1.080388	...	4.278222	13.298083	NaN	NaN	NaN	2.291371	1.989806	-0.395701	1.111020	0.954491
	2023-01-30	-0.161589	-0.119212	-0.485579	-4.350704	2.349619	-0.752434	-1.263825	0.264184	-0.125579	0.428520	...	3.914207	12.830232	NaN	NaN	NaN	2.034340	1.744189	-0.580326	1.174657	0.980863
	2023-01-31	-0.249149	-0.111299	0.580837	-4.311461	2.125479	-0.522978	-1.269708	0.149615	-0.414614	0.261126	...	3.783427	12.366186	NaN	NaN	NaN	4.748344	1.502847	-0.460303	0.904349	1.675340
	2023-02-01	-0.244308	-0.094077	0.989772	-4.181594	1.518413	0.031954	-1.081082	-0.362750	-0.399329	-0.516374	...	3.643406	11.642035	NaN	NaN	NaN	4.397930	1.416109	-0.632037	0.675453	1.989817
	2023-02-02	-0.149381	-0.069716	0.750863	-4.240031	1.322263	0.358174	-1.178853	-0.400854	-0.460727	-1.164629	...	4.035154	11.790204	NaN	NaN	NaN	4.403098	1.457429	-0.582638	0.422889	2.240189
	2023-02-03	-0.324321	-0.017821	0.742932	-4.099188	1.124398	0.400221	-1.095826	-0.374888	-0.115109	-1.262224	...	4.065579	11.408996	NaN	NaN	NaN	4.189308	1.342988	-0.645231	0.394539	2.069732
	2023-02-06	-0.267734	0.007991	0.769199	-4.068778	0.035837	0.471708	-1.089275	-0.295580	-0.071036	-1.311063	...	4.203574	10.955787	NaN	NaN	NaN	4.184727	1.200537	-0.776995	0.282424	1.927306

40 rows × 5068 columns

fr.read_factor(['球队硬币','云开雾散'],trade_date=20230106)

正在读取球队硬币因子的数据
正在读取云开雾散因子的数据

		000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	...	301398.SZ	600038.SH	600459.SH	600663.SH	600729.SH	603029.SH	688141.SH	688147.SH	688172.SH	688498.SH
name	index
球队硬币因子	2023-01-06	-3.45854	-0.674148	0.220243	-0.950252	8.786346	0.500339	-1.828122	0.267091	-0.781898	2.299623	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
云开雾散因子	2023-01-06	-0.29115	-0.524840	-1.476704	-3.120565	3.906959	-1.295554	-1.253691	-0.280816	0.352601	2.508948	...	2.564407	-0.250353	0.183853	1.403672	-0.088864	10.332152	-0.121816	0.644811	1.282682	0.950078

2 rows × 5032 columns

fr.read_factor(['球队硬币','云开雾散','飞蛾扑火'],start_date=pd.Timestamp('20230101'),end_date=20230106,sql_like=True) # 以sql的形式，分别读取球队硬币因子、云开雾散因子、飞蛾扑火因子从2023年1月1日至2023年1月13日的因子数据

正在读取球队硬币因子的数据
正在读取云开雾散因子的数据
正在读取飞蛾扑火因子的数据

	date	code	球队硬币因子	云开雾散因子	飞蛾扑火因子
0	2023-01-03	000001.SZ	-2.358642	-0.981326	-1.211546
1	2023-01-03	000002.SZ	-1.345033	-0.944349	-0.747704
2	2023-01-03	000004.SZ	1.162492	-0.997003	-1.218871
3	2023-01-03	000005.SZ	0.007223	4.198288	-0.089553
4	2023-01-03	000006.SZ	8.697314	3.824620	6.631622
...	...	...	...	...	...
20114	2023-01-06	688498.SH	NaN	0.950078	5.589459
20115	2023-01-04	000153.SZ	NaN	NaN	3.513004
20116	2023-01-05	000153.SZ	NaN	NaN	4.299205
20117	2023-01-06	000153.SZ	NaN	NaN	2.936270
20118	2023-01-06	601136.SH	NaN	NaN	4.224534

20119 rows × 5 columns

fr.read_factor(['球队硬币','云开雾散','飞蛾扑火'],trade_date=20230106,sql_like=True) # 以sql的形式，分别读取球队硬币因子、云开雾散因子、飞蛾扑火因子2023年1月13日的因子数据

正在读取球队硬币因子的数据
正在读取云开雾散因子的数据
正在读取飞蛾扑火因子的数据

	date	code	球队硬币因子	云开雾散因子	飞蛾扑火因子
0	2023-01-06	000001.SZ	-3.458540	-0.291150	-0.952147
1	2023-01-06	000002.SZ	-0.674148	-0.524840	-0.743429
2	2023-01-06	000004.SZ	0.220243	-1.476704	-1.224969
3	2023-01-06	000005.SZ	-0.950252	-3.120565	-0.757643
4	2023-01-06	000006.SZ	8.786346	3.906959	6.767050
...	...	...	...	...	...
5029	2023-01-06	688147.SH	NaN	0.644811	NaN
5030	2023-01-06	688172.SH	NaN	1.282682	0.124283
5031	2023-01-06	688498.SH	NaN	0.950078	5.589459
5032	2023-01-06	000153.SZ	NaN	NaN	2.936270
5033	2023-01-06	601136.SH	NaN	NaN	4.224534

5034 rows × 5 columns