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Tushare财经数据调取方法（行情数据）

發布時間：2023/12/16 编程问答 30 豆豆

生活随笔收集整理的這篇文章主要介紹了 Tushare财经数据调取方法（行情数据）小編覺得挺不錯的,現在分享給大家,幫大家做個參考.

Tushare財經數據調取方法（行情數據）

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二、行情數據

1.日線行情：本接口是未復權行情，停牌期間不提供數據。

import tushare as ts pro = ts.pro_api() #單個股票 df = pro.daily(ts_code='000001.SZ', start_date='20180701', end_date='20180718') df ts_codetrade_dateopenhighlowclosepre_closechangepct_chgvolamount

0	000001.SZ	20180718	8.75	8.85	8.69	8.70	8.72	-0.02	-0.23	525152.77	460697.377
1	000001.SZ	20180717	8.74	8.75	8.66	8.72	8.73	-0.01	-0.11	375356.33	326396.994
2	000001.SZ	20180716	8.85	8.90	8.69	8.73	8.88	-0.15	-1.69	689845.58	603427.713
3	000001.SZ	20180713	8.92	8.94	8.82	8.88	8.88	0.00	0.00	603378.21	535401.175
4	000001.SZ	20180712	8.60	8.97	8.58	8.88	8.64	0.24	2.78	1140492.31	1008658.828
5	000001.SZ	20180711	8.76	8.83	8.68	8.78	8.98	-0.20	-2.23	851296.70	744765.824
6	000001.SZ	20180710	9.02	9.02	8.89	8.98	9.03	-0.05	-0.55	896862.02	803038.965
7	000001.SZ	20180709	8.69	9.03	8.68	9.03	8.66	0.37	4.27	1409954.60	1255007.609
8	000001.SZ	20180706	8.61	8.78	8.45	8.66	8.60	0.06	0.70	988282.69	852071.526
9	000001.SZ	20180705	8.62	8.73	8.55	8.60	8.61	-0.01	-0.12	835768.77	722169.579
10	000001.SZ	20180704	8.63	8.75	8.61	8.61	8.67	-0.06	-0.69	711153.37	617278.559
11	000001.SZ	20180703	8.69	8.70	8.45	8.67	8.61	0.06	0.70	1274838.57	1096657.033
12	000001.SZ	20180702	9.05	9.05	8.55	8.61	9.09	-0.48	-5.28	1315520.13	1158545.868

#多個股票 df = pro.daily(ts_code='000001.SZ,600000.SH', start_date='20180701', end_date='20180718') df ts_codetrade_dateopenhighlowclosepre_closechangepct_chgvolamount

0	600000.SH	20180718	9.51	9.64	9.48	9.51	9.44	0.07	0.74	189227.00	180858.003
1	000001.SZ	20180718	8.75	8.85	8.69	8.70	8.72	-0.02	-0.23	525152.77	460697.377
2	000001.SZ	20180717	8.74	8.75	8.66	8.72	8.73	-0.01	-0.11	375356.33	326396.994
3	600000.SH	20180717	9.41	9.48	9.38	9.44	9.41	0.03	0.32	137134.95	129512.091
4	000001.SZ	20180716	8.85	8.90	8.69	8.73	8.88	-0.15	-1.69	689845.58	603427.713
5	600000.SH	20180716	9.50	9.54	9.34	9.41	9.49	-0.08	-0.84	144141.19	135697.106
6	600000.SH	20180713	9.57	9.58	9.46	9.49	9.47	0.02	0.21	150263.39	142708.347
7	000001.SZ	20180713	8.92	8.94	8.82	8.88	8.88	0.00	0.00	603378.21	535401.175
8	000001.SZ	20180712	8.60	8.97	8.58	8.88	8.64	0.24	2.78	1140492.31	1008658.828
9	600000.SH	20180712	9.41	9.61	9.39	9.57	9.38	0.19	2.03	197048.37	188206.858
10	000001.SZ	20180711	8.76	8.83	8.68	8.78	8.98	-0.20	-2.23	851296.70	744765.824
11	600000.SH	20180711	9.37	9.44	9.32	9.38	9.57	-0.19	-1.99	152039.33	142450.919
12	000001.SZ	20180710	9.02	9.02	8.89	8.98	9.03	-0.05	-0.55	896862.02	803038.965
13	600000.SH	20180710	9.61	9.65	9.50	9.57	9.60	-0.03	-0.31	124028.37	118668.133
14	000001.SZ	20180709	8.69	9.03	8.68	9.03	8.66	0.37	4.27	1409954.60	1255007.609
15	600000.SH	20180709	9.37	9.63	9.37	9.60	9.37	0.23	2.45	221725.65	212109.327
16	600000.SH	20180706	9.31	9.43	9.17	9.37	9.26	0.11	1.19	225944.43	210564.106
17	000001.SZ	20180706	8.61	8.78	8.45	8.66	8.60	0.06	0.70	988282.69	852071.526
18	600000.SH	20180705	9.26	9.35	9.22	9.26	9.31	-0.05	-0.54	164954.38	152978.661
19	000001.SZ	20180705	8.62	8.73	8.55	8.60	8.61	-0.01	-0.12	835768.77	722169.579
20	600000.SH	20180704	9.34	9.42	9.28	9.31	9.35	-0.04	-0.43	144647.77	135000.876
21	000001.SZ	20180704	8.63	8.75	8.61	8.61	8.67	-0.06	-0.69	711153.37	617278.559
22	000001.SZ	20180703	8.69	8.70	8.45	8.67	8.61	0.06	0.70	1274838.57	1096657.033
23	600000.SH	20180703	9.29	9.38	9.20	9.35	9.29	0.06	0.65	241235.51	224816.757
24	600000.SH	20180702	9.55	9.55	9.23	9.29	9.56	-0.27	-2.82	226690.89	212743.905
25	000001.SZ	20180702	9.05	9.05	8.55	8.61	9.09	-0.48	-5.28	1315520.13	1158545.868

2.周線行情：獲取A股周線行情

df = pro.weekly(ts_code='000001.SZ', start_date='20180101', end_date='20181101', fields='ts_code,trade_date,open,high,low,close,vol,amount') df ts_codetrade_datecloseopenhighlowvolamount

0	000001.SZ	20181026	11.18	10.81	11.46	10.71	9.062500e+08	1.002282e+10
1	000001.SZ	20181019	10.76	10.39	10.78	9.92	7.235320e+08	7.482596e+09
2	000001.SZ	20181012	10.30	10.70	10.79	9.70	7.257597e+08	7.483906e+09
3	000001.SZ	20180928	11.05	10.52	11.27	10.48	5.458134e+08	5.904901e+09
4	000001.SZ	20180921	10.67	9.80	10.70	9.68	5.120305e+08	5.225262e+09
5	000001.SZ	20180914	9.84	10.01	10.10	9.81	3.534262e+08	3.501724e+09
6	000001.SZ	20180907	10.01	10.09	10.55	9.93	4.708304e+08	4.796533e+09
7	000001.SZ	20180831	10.13	10.02	10.43	9.97	6.715868e+08	6.858804e+09
8	000001.SZ	20180824	10.03	8.90	10.28	8.87	6.697714e+08	6.358840e+09
9	000001.SZ	20180817	8.81	9.12	9.16	8.64	3.206923e+08	2.854248e+09
10	000001.SZ	20180810	9.23	8.94	9.35	8.88	3.054339e+08	2.787629e+09
11	000001.SZ	20180803	8.91	9.32	9.50	8.88	3.648566e+08	3.363448e+09
12	000001.SZ	20180727	9.25	9.04	9.59	9.00	5.170189e+08	4.826484e+09
13	000001.SZ	20180720	9.11	8.85	9.20	8.61	3.806004e+08	3.371040e+09
14	000001.SZ	20180713	8.88	8.69	9.03	8.58	4.901984e+08	4.346872e+09
15	000001.SZ	20180706	8.66	9.05	9.05	8.45	5.125564e+08	4.446723e+09
16	000001.SZ	20180629	9.09	9.91	9.92	8.87	5.150576e+08	4.764107e+09
17	000001.SZ	20180622	9.85	10.05	10.15	9.76	3.827401e+08	3.800475e+09
18	000001.SZ	20180615	10.17	10.06	10.29	9.92	4.280360e+08	4.315074e+09
19	000001.SZ	20180608	10.12	10.23	10.46	10.06	4.324341e+08	4.424459e+09
20	000001.SZ	20180601	10.19	10.58	10.66	10.02	4.167914e+08	4.280512e+09
21	000001.SZ	20180525	10.59	11.07	11.11	10.55	3.625909e+08	3.897568e+09
22	000001.SZ	20180518	10.96	11.09	11.23	10.76	3.587800e+08	3.947275e+09
23	000001.SZ	20180511	11.01	10.70	11.15	10.64	4.300377e+08	4.705948e+09
24	000001.SZ	20180504	10.68	10.97	11.03	10.57	3.182388e+08	3.429873e+09
25	000001.SZ	20180427	10.85	11.30	11.94	10.63	6.845706e+08	7.769357e+09
26	000001.SZ	20180420	11.35	11.47	11.69	11.03	6.012632e+08	6.824983e+09
27	000001.SZ	20180413	11.57	10.80	11.92	10.73	7.035101e+08	8.082163e+09
28	000001.SZ	20180404	10.87	10.87	11.01	10.51	3.602551e+08	3.880409e+09
29	000001.SZ	20180330	10.90	11.15	11.20	10.55	5.669332e+08	6.203168e+09
30	000001.SZ	20180323	11.34	11.66	12.12	10.92	5.839767e+08	6.794436e+09
31	000001.SZ	20180316	11.64	12.15	12.22	11.64	5.105241e+08	6.080941e+09
32	000001.SZ	20180309	12.09	11.93	12.34	11.77	4.965548e+08	5.985965e+09
33	000001.SZ	20180302	11.95	12.77	12.85	11.85	5.095855e+08	6.233384e+09
34	000001.SZ	20180223	12.61	12.25	12.79	12.25	2.282069e+08	2.851748e+09
35	000001.SZ	20180214	12.00	11.78	12.21	11.56	3.391151e+08	4.032539e+09
36	000001.SZ	20180209	11.69	13.80	14.57	11.38	1.322335e+09	1.750926e+10
37	000001.SZ	20180202	14.05	14.05	14.30	13.53	8.115143e+08	1.129147e+10
38	000001.SZ	20180126	14.05	14.60	15.08	14.00	1.145692e+09	1.660992e+10
39	000001.SZ	20180119	14.80	13.51	15.13	13.50	1.294241e+09	1.865851e+10
40	000001.SZ	20180112	13.55	13.25	13.68	12.86	8.704112e+08	1.152740e+10
41	000001.SZ	20180105	13.30	13.35	13.93	13.13	8.108913e+08	1.092060e+10

df = pro.weekly(trade_date='20181123', fields='ts_code,trade_date,open,high,low,close,vol,amount') df ts_codetrade_datecloseopenhighlowvolamount

0	000001.SZ	20181123	10.32	10.57	10.88	10.31	426154795.0	4.529963e+09
1	000002.SZ	20181123	24.90	24.70	26.68	24.68	224382883.0	5.769860e+09
2	000004.SZ	20181123	16.49	17.49	18.15	16.49	2658044.0	4.556597e+07
3	000005.SZ	20181123	2.90	3.17	3.22	2.88	59830345.0	1.832934e+08
4	000006.SZ	20181123	5.27	5.67	5.94	5.25	123699441.0	6.935153e+08
...	...	...	...	...	...	...	...	...
3522	603993.SH	20181123	3.87	4.16	4.23	3.85	537540699.0	2.189281e+09
3523	603996.SH	20181123	8.11	8.94	9.13	7.96	28956289.0	2.527451e+08
3524	603997.SH	20181123	8.43	8.36	8.72	7.88	19952764.0	1.676455e+08
3525	603998.SH	20181123	5.26	5.77	5.86	5.21	34548883.0	1.947678e+08
3526	603999.SH	20181123	5.20	5.27	5.45	4.98	30761287.0	1.614327e+08

3527 rows × 8 columns

3.月線行情:獲取A股月線數據

df = pro.monthly(ts_code='000001.SZ', start_date='20180101', end_date='20181101', fields='ts_code,trade_date,open,high,low,close,vol,amount') df ts_codetrade_datecloseopenhighlowvolamount

0	000001.SZ	20181031	10.91	10.70	11.46	9.70	2.780156e+09	2.960878e+10
1	000001.SZ	20180928	11.05	10.09	11.27	9.68	1.882100e+09	1.942842e+10
2	000001.SZ	20180831	10.13	9.42	10.43	8.64	2.189687e+09	2.088672e+10
3	000001.SZ	20180731	9.42	9.05	9.59	8.45	2.043028e+09	1.832737e+10
4	000001.SZ	20180629	9.09	10.15	10.46	8.87	1.817989e+09	1.791251e+10
5	000001.SZ	20180531	10.18	10.97	11.23	10.02	1.826718e+09	1.965278e+10
6	000001.SZ	20180427	10.85	10.87	11.94	10.51	2.349599e+09	2.655691e+10
7	000001.SZ	20180330	10.90	11.92	12.34	10.55	2.312997e+09	2.692560e+10
8	000001.SZ	20180228	12.05	13.95	14.57	11.38	2.562447e+09	3.322504e+10
9	000001.SZ	20180131	14.05	13.35	15.13	12.86	4.614538e+09	6.454870e+10

df = pro.monthly(trade_date='20181031', fields='ts_code,trade_date,open,high,low,close,vol,amount') df ts_codetrade_datecloseopenhighlowvolamount

0	000001.SZ	20181031	10.91	10.70	11.46	9.70	2.780156e+09	2.960878e+10
1	000002.SZ	20181031	24.23	22.95	24.75	20.40	1.131501e+09	2.528377e+10
2	000004.SZ	20181031	15.54	17.49	17.49	14.70	3.690866e+06	5.919159e+07
3	000005.SZ	20181031	2.73	2.90	2.91	2.42	1.251723e+08	3.426416e+08
4	000006.SZ	20181031	5.07	5.49	5.49	4.51	3.302938e+08	1.650338e+09
...	...	...	...	...	...	...	...	...
3506	603993.SH	20181031	4.07	4.45	4.47	3.44	2.220735e+09	8.620470e+09
3507	603996.SH	20181031	7.78	8.64	8.70	6.72	1.074282e+08	8.123262e+08
3508	603997.SH	20181031	8.29	9.78	9.78	7.20	1.047243e+08	8.530102e+08
3509	603998.SH	20181031	5.00	5.74	5.74	4.53	5.361062e+07	2.659748e+08
3510	603999.SH	20181031	4.82	5.08	5.75	3.94	1.155360e+08	5.708665e+08

3511 rows × 8 columns

4.A股復權行情

#取000001的前復權行情 df = ts.pro_bar(ts_code='000001.SZ', adj='qfq', start_date='20180101', end_date='20181011') df ts_codetrade_dateopenhighlowclosepre_closechangepct_chgvolamount

0	000001.SZ	20181011	10.0500	10.1600	9.7000	9.8600	10.4500	-0.5900	-5.6459	1995143.83	1994186.611
1	000001.SZ	20181010	10.5400	10.6600	10.3800	10.4500	10.5600	-0.1100	-1.0417	995200.08	1045666.180
2	000001.SZ	20181009	10.4600	10.7000	10.3900	10.5600	10.4500	0.1100	1.0526	1064084.26	1117946.550
3	000001.SZ	20181008	10.7000	10.7900	10.4500	10.4500	11.0500	-0.6000	-5.4299	1686358.52	1793455.283
4	000001.SZ	20180928	10.7800	11.2700	10.7800	11.0500	10.7400	0.3100	2.8864	2110242.67	2331358.288
...	...	...	...	...	...	...	...	...	...	...	...
182	000001.SZ	20180108	13.0388	13.0782	12.6550	12.7534	13.0880	-0.3346	-2.5565	2158620.81	2806099.169
183	000001.SZ	20180105	12.9994	13.1372	12.9404	13.0880	13.0388	0.0492	0.3773	1210312.72	1603289.517
184	000001.SZ	20180104	13.1077	13.1569	12.9207	13.0388	13.1175	-0.0787	-0.6000	1854509.48	2454543.516
185	000001.SZ	20180103	13.5111	13.6391	12.9896	13.1175	13.4816	-0.3641	-2.7007	2962498.38	4006220.766
186	000001.SZ	20180102	13.1372	13.7080	13.1077	13.4816	13.0880	0.3936	3.0073	2081592.55	2856543.822

187 rows × 11 columns

#取000001的后復權行情 df = ts.pro_bar(ts_code='000001.SZ', adj='hfq', start_date='20180101', end_date='20181011') df ts_codetrade_dateopenhighlowclosepre_closechangepct_chgvolamount

0	000001.SZ	20181011	1085.7116	1097.5950	1047.9007	1065.1857	1128.9239	-63.7382	-5.6459	1995143.83	1994186.611
1	000001.SZ	20181010	1138.6467	1151.6105	1121.3618	1128.9239	1140.8074	-11.8835	-1.0417	995200.08	1045666.180
2	000001.SZ	20181009	1130.0043	1155.9317	1122.4421	1140.8074	1128.9239	11.8835	1.0526	1064084.26	1117946.550
3	000001.SZ	20181008	1155.9317	1165.6545	1128.9239	1128.9239	1193.7426	-64.8187	-5.4299	1686358.52	1793455.283
4	000001.SZ	20180928	1164.5742	1217.5094	1164.5742	1193.7426	1160.2529	33.4897	2.8864	2110242.67	2331358.288
...	...	...	...	...	...	...	...	...	...	...	...
182	000001.SZ	20180108	1408.5942	1412.8466	1367.1337	1377.7646	1413.9097	-36.1451	-2.5564	2158620.81	2806099.169
183	000001.SZ	20180105	1404.3419	1419.2251	1397.9633	1413.9097	1408.5942	5.3155	0.3774	1210312.72	1603289.517
184	000001.SZ	20180104	1416.0359	1421.3513	1395.8372	1408.5942	1417.0990	-8.5048	-0.6002	1854509.48	2454543.516
185	000001.SZ	20180103	1459.6226	1473.4427	1403.2788	1417.0990	1456.4333	-39.3343	-2.7007	2962498.38	4006220.766
186	000001.SZ	20180102	1419.2251	1480.8844	1416.0359	1456.4333	1413.9097	42.5236	3.0075	2081592.55	2856543.822

187 rows × 11 columns

#取000001的周線前復權行情 df = ts.pro_bar( ts_code='000001.SZ', freq='W', adj='qfq', start_date='20180101', end_date='20181011') df ts_codetrade_datecloseopenhighlowpre_closechangepct_chgvolamount

0	000001.SZ	20180928	11.0500	10.5200	11.2700	10.4800	10.6700	0.3800	3.5614	5.458134e+08	5.904901e+09
1	000001.SZ	20180921	10.6700	9.8000	10.7000	9.6800	9.8400	0.8300	8.4350	5.120305e+08	5.225262e+09
2	000001.SZ	20180914	9.8400	10.0100	10.1000	9.8100	10.0100	-0.1700	-1.6983	3.534262e+08	3.501724e+09
3	000001.SZ	20180907	10.0100	10.0900	10.5500	9.9300	10.1300	-0.1200	-1.1846	4.708304e+08	4.796533e+09
4	000001.SZ	20180831	10.1300	10.0200	10.4300	9.9700	10.0300	0.1000	0.9970	6.715868e+08	6.858804e+09
5	000001.SZ	20180824	10.0300	8.9000	10.2800	8.8700	8.8100	1.2200	13.8479	6.697714e+08	6.358840e+09
6	000001.SZ	20180817	8.8100	9.1200	9.1600	8.6400	9.2300	-0.4200	-4.5504	3.206923e+08	2.854248e+09
7	000001.SZ	20180810	9.2300	8.9400	9.3500	8.8800	8.9100	0.3200	3.5915	3.054339e+08	2.787629e+09
8	000001.SZ	20180803	8.9100	9.3200	9.5000	8.8800	9.2500	-0.3400	-3.6757	3.648566e+08	3.363448e+09
9	000001.SZ	20180727	9.2500	9.0400	9.5900	9.0000	9.1100	0.1400	1.5368	5.170189e+08	4.826484e+09
10	000001.SZ	20180720	9.1100	8.8500	9.2000	8.6100	8.8800	0.2300	2.5901	3.806004e+08	3.371040e+09
11	000001.SZ	20180713	8.8800	8.6900	9.0300	8.5800	8.6600	0.2200	2.5404	4.901984e+08	4.346872e+09
12	000001.SZ	20180706	8.5220	8.9057	8.9057	8.3153	8.9451	-0.4231	-4.7300	5.125564e+08	4.446723e+09
13	000001.SZ	20180629	8.9451	9.7520	9.7619	8.7286	9.6930	-0.7479	-7.7159	5.150576e+08	4.764107e+09
14	000001.SZ	20180622	9.6930	9.8898	9.9882	9.6044	10.0079	-0.3149	-3.1465	3.827401e+08	3.800475e+09
15	000001.SZ	20180615	10.0079	9.8996	10.1260	9.7619	9.9587	0.0492	0.4940	4.280360e+08	4.315074e+09
16	000001.SZ	20180608	9.9587	10.0669	10.2933	9.8996	10.0276	-0.0689	-0.6871	4.324341e+08	4.424459e+09
17	000001.SZ	20180601	10.0276	10.4114	10.4901	9.8603	10.4212	-0.3936	-3.7769	4.167914e+08	4.280512e+09
18	000001.SZ	20180525	10.4212	10.8935	10.9329	10.3818	10.7853	-0.3641	-3.3759	3.625909e+08	3.897568e+09
19	000001.SZ	20180518	10.7853	10.9132	11.0510	10.5885	10.8345	-0.0492	-0.4541	3.587800e+08	3.947275e+09
20	000001.SZ	20180511	10.8345	10.5294	10.9723	10.4704	10.5098	0.3247	3.0895	4.300377e+08	4.705948e+09
21	000001.SZ	20180504	10.5098	10.7951	10.8542	10.4015	10.6771	-0.1673	-1.5669	3.182388e+08	3.429873e+09
22	000001.SZ	20180427	10.6771	11.1199	11.7497	10.4606	11.1691	-0.4920	-4.4050	6.845706e+08	7.769357e+09
23	000001.SZ	20180420	11.1691	11.2872	11.5037	10.8542	11.3856	-0.2165	-1.9015	6.012632e+08	6.824983e+09
24	000001.SZ	20180413	11.3856	10.6278	11.7300	10.5590	10.6967	0.6889	6.4403	7.035101e+08	8.082163e+09
25	000001.SZ	20180404	10.6967	10.6967	10.8345	10.3425	10.7263	-0.0296	-0.2760	3.602551e+08	3.880409e+09
26	000001.SZ	20180330	10.7263	10.9723	11.0215	10.3818	11.1592	-0.4329	-3.8793	5.669332e+08	6.203168e+09
27	000001.SZ	20180323	11.1592	11.4741	11.9268	10.7459	11.4545	-0.2953	-2.5780	5.839767e+08	6.794436e+09
28	000001.SZ	20180316	11.4545	11.9563	12.0252	11.4545	11.8973	-0.4428	-3.7219	5.105241e+08	6.080941e+09
29	000001.SZ	20180309	11.8973	11.7398	12.1433	11.5824	11.7595	0.1378	1.1718	4.965548e+08	5.985965e+09
30	000001.SZ	20180302	11.7595	12.5664	12.6452	11.6611	12.4090	-0.6495	-5.2341	5.095855e+08	6.233384e+09
31	000001.SZ	20180223	12.4090	12.0547	12.5861	12.0547	11.8087	0.6003	5.0835	2.282069e+08	2.851748e+09
32	000001.SZ	20180214	11.8087	11.5922	12.0154	11.3757	11.5037	0.3050	2.6513	3.391151e+08	4.032539e+09
33	000001.SZ	20180209	11.5037	13.5800	14.3378	11.1986	13.8260	-2.3223	-16.7966	1.322335e+09	1.750926e+10
34	000001.SZ	20180202	13.8260	13.8260	14.0721	13.3143	13.8260	0.0000	0.0000	8.115143e+08	1.129147e+10
35	000001.SZ	20180126	13.8260	14.3673	14.8396	13.7768	14.5641	-0.7381	-5.0679	1.145692e+09	1.660992e+10
36	000001.SZ	20180119	14.5641	13.2947	14.8888	13.2848	13.3340	1.2301	9.2253	1.294241e+09	1.865851e+10
37	000001.SZ	20180112	13.3340	13.0388	13.4619	12.6550	13.0880	0.2460	1.8796	8.704112e+08	1.152740e+10
38	000001.SZ	20180105	13.0880	13.1372	13.7080	12.9207	13.0880	0.0000	0.0000	8.108913e+08	1.092060e+10

#取000001的周線后復權行情 df = ts.pro_bar(ts_code='000001.SZ', freq='W', adj='hfq', start_date='20180101', end_date='20181011') df ts_codetrade_datecloseopenhighlowpre_closechangepct_chgvolamount

0	000001.SZ	20180928	1193.7426	1136.4861	1217.5094	1132.1649	1152.6908	41.0518	3.5614	5.458134e+08	5.904901e+09
1	000001.SZ	20180921	1152.6908	1058.7038	1155.9317	1045.7401	1063.0250	89.6658	8.4350	5.120305e+08	5.225262e+09
2	000001.SZ	20180914	1063.0250	1081.3903	1091.1131	1059.7841	1081.3903	-18.3653	-1.6983	3.534262e+08	3.501724e+09
3	000001.SZ	20180907	1081.3903	1090.0328	1139.7271	1072.7478	1094.3540	-12.9637	-1.1846	4.708304e+08	4.796533e+09
4	000001.SZ	20180831	1094.3540	1082.4706	1126.7633	1077.0691	1083.5509	10.8031	0.9970	6.715868e+08	6.858804e+09
5	000001.SZ	20180824	1083.5509	961.4759	1110.5587	958.2350	951.7531	131.7978	13.8479	6.697714e+08	6.358840e+09
6	000001.SZ	20180817	951.7531	985.2427	989.5640	933.3878	997.1261	-45.3730	-4.5504	3.206923e+08	2.854248e+09
7	000001.SZ	20180810	997.1261	965.7971	1010.0899	959.3153	962.5562	34.5699	3.5915	3.054339e+08	2.787629e+09
8	000001.SZ	20180803	962.5562	1006.8489	1026.2945	959.3153	999.2868	-36.7306	-3.6757	3.648566e+08	3.363448e+09
9	000001.SZ	20180727	999.2868	976.6002	1036.0173	972.2790	984.1624	15.1244	1.5368	5.170189e+08	4.826484e+09
10	000001.SZ	20180720	984.1624	956.0743	993.8852	930.1469	959.3153	24.8471	2.5901	3.806004e+08	3.371040e+09
11	000001.SZ	20180713	959.3153	938.7894	975.5199	926.9060	935.5485	23.7668	2.5404	4.901984e+08	4.346872e+09
12	000001.SZ	20180706	920.6359	962.0965	962.0965	898.3110	966.3488	-45.7129	-4.7305	5.125564e+08	4.446723e+09
13	000001.SZ	20180629	966.3488	1053.5222	1054.5853	942.9608	1047.1436	-80.7948	-7.7157	5.150576e+08	4.764107e+09
14	000001.SZ	20180622	1047.1436	1068.4054	1079.0364	1037.5758	1081.1625	-34.0189	-3.1465	3.827401e+08	3.800475e+09
15	000001.SZ	20180615	1081.1625	1069.4685	1093.9196	1054.5853	1075.8471	5.3154	0.4941	4.280360e+08	4.315074e+09
16	000001.SZ	20180608	1075.8471	1087.5411	1111.9921	1069.4685	1083.2887	-7.4416	-0.6869	4.324341e+08	4.424459e+09
17	000001.SZ	20180601	1083.2887	1124.7492	1133.2539	1065.2162	1125.8123	-42.5236	-3.7771	4.167914e+08	4.280512e+09
18	000001.SZ	20180525	1125.8123	1176.8406	1181.0930	1121.5600	1165.1466	-39.3343	-3.3759	3.625909e+08	3.897568e+09
19	000001.SZ	20180518	1165.1466	1178.9668	1193.8501	1143.8848	1170.4621	-5.3155	-0.4541	3.587800e+08	3.947275e+09
20	000001.SZ	20180511	1170.4621	1137.5063	1185.3454	1131.1278	1135.3801	35.0820	3.0899	4.300377e+08	4.705948e+09
21	000001.SZ	20180504	1135.3801	1166.2097	1172.5883	1123.6861	1153.4526	-18.0725	-1.5668	3.182388e+08	3.429873e+09
22	000001.SZ	20180427	1153.4526	1201.2917	1269.3295	1130.0647	1206.6072	-53.1546	-4.4053	6.845706e+08	7.769357e+09
23	000001.SZ	20180420	1206.6072	1219.3642	1242.7522	1172.5883	1229.9951	-23.3879	-1.9015	6.012632e+08	6.824983e+09
24	000001.SZ	20180413	1229.9951	1148.1372	1267.2033	1140.6956	1155.5788	74.4163	6.4397	7.035101e+08	8.082163e+09
25	000001.SZ	20180404	1155.5788	1155.5788	1170.4621	1117.3076	1158.7681	-3.1893	-0.2752	3.602551e+08	3.880409e+09
26	000001.SZ	20180330	1158.7681	1185.3454	1190.6608	1121.5600	1205.5441	-46.7760	-3.8801	5.669332e+08	6.203168e+09
27	000001.SZ	20180323	1205.5441	1239.5629	1288.4651	1160.8943	1237.4368	-31.8927	-2.5773	5.839767e+08	6.794436e+09
28	000001.SZ	20180316	1237.4368	1291.6544	1299.0960	1237.4368	1285.2758	-47.8390	-3.7221	5.105241e+08	6.080941e+09
29	000001.SZ	20180309	1285.2758	1268.2664	1311.8531	1251.2569	1270.3925	14.8833	1.1716	4.965548e+08	5.985965e+09
30	000001.SZ	20180302	1270.3925	1357.5659	1366.0706	1259.7616	1340.5565	-70.1640	-5.2339	5.095855e+08	6.233384e+09
31	000001.SZ	20180223	1340.5565	1302.2852	1359.6921	1302.2852	1275.7080	64.8485	5.0833	2.282069e+08	2.851748e+09
32	000001.SZ	20180214	1275.7080	1252.3200	1298.0329	1228.9320	1242.7522	32.9558	2.6518	3.391151e+08	4.032539e+09
33	000001.SZ	20180209	1242.7522	1467.0642	1548.9221	1209.7964	1493.6415	-250.8893	-16.7972	1.322335e+09	1.750926e+10
34	000001.SZ	20180202	1493.6415	1493.6415	1520.2187	1438.3608	1493.6415	0.0000	0.0000	8.115143e+08	1.129147e+10
35	000001.SZ	20180126	1493.6415	1552.1114	1603.1397	1488.3260	1573.3732	-79.7317	-5.0676	1.145692e+09	1.660992e+10
36	000001.SZ	20180119	1573.3732	1436.2346	1608.4552	1435.1715	1440.4869	132.8863	9.2251	1.294241e+09	1.865851e+10
37	000001.SZ	20180112	1440.4869	1408.5942	1454.3071	1367.1337	1413.9097	26.5772	1.8797	8.704112e+08	1.152740e+10
38	000001.SZ	20180105	1413.9097	1419.2251	1480.8844	1395.8372	1413.9097	0.0000	0.0000	8.108913e+08	1.092060e+10

#取000001的月線前復權行情 df = ts.pro_bar(ts_code='000001.SZ', freq='M', adj='qfq', start_date='20180101', end_date='20181011') df ts_codetrade_datecloseopenhighlowpre_closechangepct_chgvolamount

0	000001.SZ	20180928	11.0500	10.0900	11.2700	9.6800	10.1300	0.9200	9.0819	1.882100e+09	1.942842e+10
1	000001.SZ	20180831	10.1300	9.4200	10.4300	8.6400	9.4200	0.7100	7.5372	2.189687e+09	2.088672e+10
2	000001.SZ	20180731	9.4200	9.0500	9.5900	8.4500	9.0900	0.3300	3.6304	2.043028e+09	1.832737e+10
3	000001.SZ	20180629	8.9451	9.9882	10.2933	8.7286	10.0177	-1.0726	-10.7070	1.817989e+09	1.791251e+10
4	000001.SZ	20180531	10.0177	10.7951	11.0510	9.8603	10.6771	-0.6594	-6.1758	1.826718e+09	1.965278e+10
5	000001.SZ	20180427	10.6771	10.6967	11.7497	10.3425	10.7263	-0.0492	-0.4587	2.349599e+09	2.655691e+10
6	000001.SZ	20180330	10.7263	11.7300	12.1433	10.3818	11.8579	-1.1316	-9.5430	2.312997e+09	2.692560e+10
7	000001.SZ	20180228	11.8579	13.7276	14.3378	11.1986	13.8260	-1.9681	-14.2348	2.562447e+09	3.322504e+10
8	000001.SZ	20180131	13.8260	13.1372	14.8888	12.6550	13.0880	0.7380	5.6388	4.614538e+09	6.454870e+10

#取000001的月線后復權行情 df = ts.pro_bar(ts_code='000001.SZ', freq='M', adj='hfq', start_date='20180101', end_date='20181011') df ts_codetrade_datecloseopenhighlowpre_closechangepct_chgvolamount

0	000001.SZ	20180928	1193.7426	1090.0328	1217.5094	1045.7401	1094.3540	99.3886	9.0819	1.882100e+09	1.942842e+10
1	000001.SZ	20180831	1094.3540	1017.6520	1126.7633	933.3878	1017.6520	76.7020	7.5372	2.189687e+09	2.088672e+10
2	000001.SZ	20180731	1017.6520	977.6806	1036.0173	912.8619	982.0018	35.6502	3.6304	2.043028e+09	1.832737e+10
3	000001.SZ	20180629	966.3488	1079.0364	1111.9921	942.9608	1082.2256	-115.8768	-10.7073	1.817989e+09	1.791251e+10
4	000001.SZ	20180531	1082.2256	1166.2097	1193.8501	1065.2162	1153.4526	-71.2270	-6.1751	1.826718e+09	1.965278e+10
5	000001.SZ	20180427	1153.4526	1155.5788	1269.3295	1117.3076	1158.7681	-5.3155	-0.4587	2.349599e+09	2.655691e+10
6	000001.SZ	20180330	1158.7681	1267.2033	1311.8531	1121.5600	1281.0235	-122.2554	-9.5436	2.312997e+09	2.692560e+10
7	000001.SZ	20180228	1281.0235	1483.0105	1548.9221	1209.7964	1493.6415	-212.6180	-14.2349	2.562447e+09	3.322504e+10
8	000001.SZ	20180131	1493.6415	1419.2251	1608.4552	1367.1337	1413.9097	79.7318	5.6391	4.614538e+09	6.454870e+10

5.復權因子

#提取000001全部復權因子 df = pro.adj_factor(ts_code='000001.SZ', trade_date='') df ts_codetrade_dateadj_factor

0	000001.SZ	20210312	111.048
1	000001.SZ	20210311	111.048
2	000001.SZ	20210310	111.048
3	000001.SZ	20210309	111.048
4	000001.SZ	20210308	111.048
...	...	...	...
4995	000001.SZ	20000804	21.662
4996	000001.SZ	20000803	21.662
4997	000001.SZ	20000802	21.662
4998	000001.SZ	20000801	21.662
4999	000001.SZ	20000731	21.662

5000 rows × 3 columns

#提取2018年7月18日復權因子 df = pro.adj_factor(ts_code='', trade_date='20180718') df ts_codetrade_dateadj_factor

0	000001.SZ	20180718	108.031
1	000002.SZ	20180718	137.300
2	000004.SZ	20180718	4.064
3	000005.SZ	20180718	9.268
4	000006.SZ	20180718	34.226
...	...	...	...
3523	603993.SH	20180718	3.269
3524	603996.SH	20180718	1.536
3525	603997.SH	20180718	1.569
3526	603998.SH	20180718	3.934
3527	603999.SH	20180718	2.436

3528 rows × 3 columns

總結

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