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1、load model

Browse Source 
2、修改update data相关函数
This commit is contained in:
liaozhaorun
2025-10-13 15:04:48 +08:00
parent f42f4e72e1
commit dc29f153ca
19 changed files with 9240 additions and 10975 deletions
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5604
main/data/daily_data.ipynb
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File diff suppressed because it is too large Load Diff

61
main/data/index_and_industry.ipynb
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@@ -2,12 +2,11 @@
"cells": [
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 1,
"id": "initial_id",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T14:57:27.092313Z",
"start_time": "2025-04-09T14:57:26.124592Z"
"jupyter": {
"is_executing": true
}
},
"outputs": [],
@@ -24,11 +23,11 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 2,
"id": "f448da220816bf98",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T14:57:37.680808Z",
"end_time": "2025-07-26T10:23:18.517518100Z",
"start_time": "2025-04-09T14:57:27.392846Z"
}
},
@@ -70,11 +69,11 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 3,
"id": "907f732d3c397bf",
"metadata": {
"ExecuteTime": {
"end_time": "2025-04-09T14:57:37.730922Z",
"end_time": "2025-07-26T10:23:18.552166300Z",
"start_time": "2025-04-09T14:57:37.695917Z"
}
},
@@ -84,32 +83,32 @@
"output_type": "stream",
"text": [
" ts_code trade_date close open high low \\\n",
"0 000905.SH 20250530 5671.0723 5704.7710 5704.7710 5665.5177 \n",
"1 000905.SH 20250529 5719.9101 5637.0633 5724.5185 5637.0633 \n",
"2 000905.SH 20250528 5637.2378 5651.8755 5660.4696 5628.4165 \n",
"3 000905.SH 20250527 5652.1454 5666.3027 5667.8710 5629.1343 \n",
"4 000905.SH 20250526 5669.4609 5653.2063 5693.6250 5644.5794 \n",
"0 000905.SH 20251010 7398.2241 7499.3917 7509.1161 7373.9841 \n",
"1 000905.SH 20251009 7548.9226 7470.0474 7559.0920 7437.3242 \n",
"2 000905.SH 20250930 7412.3684 7372.5240 7428.0307 7372.0634 \n",
"3 000905.SH 20250929 7350.5599 7251.5221 7377.2217 7216.7357 \n",
"4 000905.SH 20250926 7240.9114 7311.8433 7351.7931 7237.0459 \n",
"... ... ... ... ... ... ... \n",
"13546 399006.SZ 20100607 1069.4680 1005.0280 1075.2250 1001.7020 \n",
"13547 399006.SZ 20100604 1027.6810 989.6810 1027.6810 986.5040 \n",
"13548 399006.SZ 20100603 998.3940 1002.3550 1026.7020 997.7750 \n",
"13549 399006.SZ 20100602 997.1190 967.6090 997.1190 952.6110 \n",
"13550 399006.SZ 20100601 973.2330 986.0150 994.7930 948.1180 \n",
"13810 399006.SZ 20100607 1069.4680 1005.0280 1075.2250 1001.7020 \n",
"13811 399006.SZ 20100604 1027.6810 989.6810 1027.6810 986.5040 \n",
"13812 399006.SZ 20100603 998.3940 1002.3550 1026.7020 997.7750 \n",
"13813 399006.SZ 20100602 997.1190 967.6090 997.1190 952.6110 \n",
"13814 399006.SZ 20100601 973.2330 986.0150 994.7930 948.1180 \n",
"\n",
" pre_close change pct_chg vol amount \n",
"0 5719.9101 -48.8378 -0.8538 1.099007e+08 1.376706e+08 \n",
"1 5637.2378 82.6723 1.4665 1.146825e+08 1.480951e+08 \n",
"2 5652.1454 -14.9076 -0.2638 9.490888e+07 1.199598e+08 \n",
"3 5669.4609 -17.3155 -0.3054 9.514936e+07 1.252757e+08 \n",
"4 5653.0436 16.4173 0.2904 9.717099e+07 1.273436e+08 \n",
"... ... ... ... ... ... \n",
"13546 1027.6810 41.7870 4.0661 2.655275e+06 9.106095e+06 \n",
"13547 998.3940 29.2870 2.9334 1.500295e+06 5.269441e+06 \n",
"13548 997.1190 1.2750 0.1279 1.616805e+06 6.240835e+06 \n",
"13549 973.2330 23.8860 2.4543 1.074628e+06 4.001206e+06 \n",
"13550 1000.0000 -26.7670 -2.6767 1.356285e+06 4.924177e+06 \n",
" pre_close change pct_chg vol amount \n",
"0 7548.9226 -150.6985 -1.9963 2.622566e+08 5.021274e+08 \n",
"1 7412.3684 136.5542 1.8422 2.831308e+08 5.357568e+08 \n",
"2 7350.5599 61.8085 0.8409 2.207075e+08 4.449564e+08 \n",
"3 7240.9114 109.6485 1.5143 2.335394e+08 4.338645e+08 \n",
"4 7341.3238 -100.4124 -1.3678 2.114441e+08 4.301976e+08 \n",
"... ... ... ... ... ... \n",
"13810 1027.6810 41.7870 4.0661 2.655275e+06 9.106095e+06 \n",
"13811 998.3940 29.2870 2.9334 1.500295e+06 5.269441e+06 \n",
"13812 997.1190 1.2750 0.1279 1.616805e+06 6.240835e+06 \n",
"13813 973.2330 23.8860 2.4543 1.074628e+06 4.001206e+06 \n",
"13814 1000.0000 -26.7670 -2.6767 1.356285e+06 4.924177e+06 \n",
"\n",
"[13551 rows x 11 columns]\n"
"[13815 rows x 11 columns]\n"
]
}
],

47
main/data/update/cyq-perf.ipynb
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@@ -39,15 +39,15 @@
"3 000006.SZ 20250312\n",
"4 000007.SZ 20250312\n",
"... ... ...\n",
"26917 920445.BJ 20250519\n",
"26918 920489.BJ 20250519\n",
"26919 920682.BJ 20250519\n",
"26920 920799.BJ 20250519\n",
"26921 920819.BJ 20250519\n",
"27111 920445.BJ 20250922\n",
"27112 920489.BJ 20250922\n",
"27113 920682.BJ 20250922\n",
"27114 920799.BJ 20250922\n",
"27115 920819.BJ 20250922\n",
"\n",
"[7724334 rows x 2 columns]\n",
"20250523\n",
"start_date: 20250526\n"
"[8205543 rows x 2 columns]\n",
"20250926\n",
"start_date: 20250929\n"
]
}
],
@@ -64,7 +64,7 @@
" max_date = df['trade_date'].max()\n",
"\n",
"print(max_date)\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250620')\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20251020')\n",
"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
"trade_dates = trade_cal[trade_cal['cal_date'] > max_date]['cal_date'].tolist()\n",
"start_date = min(trade_dates)\n",
@@ -86,25 +86,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"任务 20250620 完成\n",
"任务 20250619 完成\n",
"任务 20250618 完成\n",
"任务 20250617 完成\n",
"任务 20250616 完成\n",
"任务 20250613 完成\n",
"任务 20250612 完成\n",
"任务 20250611 完成\n",
"任务 20250610 完成\n",
"任务 20250609 完成\n",
"任务 20250606 完成\n",
"任务 20250605 完成\n",
"任务 20250604 完成\n",
"任务 20250603 完成\n",
"任务 20250530 完成\n",
"任务 20250529 完成\n",
"任务 20250528 完成\n",
"任务 20250527 完成\n",
"任务 20250526 完成\n"
"任务 20251020 完成\n",
"任务 20251017 完成\n",
"任务 20251016 完成\n",
"任务 20251015 完成\n",
"任务 20251014 完成\n",
"任务 20251013 完成\n",
"任务 20251010 完成\n",
"任务 20251009 完成\n",
"任务 20250930 完成\n",
"任务 20250929 完成\n"
]
}
],

47
main/data/update/sw_daily.ipynb
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@@ -39,15 +39,15 @@
"3 801005.SI 20250221\n",
"4 801010.SI 20250221\n",
"... ... ...\n",
"2190 859811.SI 20250519\n",
"2191 859821.SI 20250519\n",
"2192 859822.SI 20250519\n",
"2193 859852.SI 20250519\n",
"2194 859951.SI 20250519\n",
"2190 859811.SI 20250922\n",
"2191 859821.SI 20250922\n",
"2192 859822.SI 20250922\n",
"2193 859852.SI 20250922\n",
"2194 859951.SI 20250922\n",
"\n",
"[1071172 rows x 2 columns]\n",
"20250523\n",
"start_date: 20250526\n"
"[1110243 rows x 2 columns]\n",
"20250926\n",
"start_date: 20250929\n"
]
}
],
@@ -64,7 +64,7 @@
" max_date = df['trade_date'].max()\n",
"\n",
"print(max_date)\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250620')\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20251020')\n",
"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
"trade_dates = trade_cal[trade_cal['cal_date'] > max_date]['cal_date'].tolist()\n",
"start_date = min(trade_dates)\n",
@@ -86,25 +86,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"任务 20250619 完成\n",
"任务 20250620 完成\n",
"任务 20250618 完成\n",
"任务 20250617 完成\n",
"任务 20250616 完成\n",
"任务 20250613 完成\n",
"任务 20250612 完成\n",
"任务 20250611 完成\n",
"任务 20250609 完成\n",
"任务 20250610 完成\n",
"任务 20250606 完成\n",
"任务 20250605 完成\n",
"任务 20250604 完成\n",
"任务 20250603 完成\n",
"任务 20250530 完成\n",
"任务 20250529 完成\n",
"任务 20250527 完成\n",
"任务 20250528 完成\n",
"任务 20250526 完成\n"
"任务 20251020 完成\n",
"任务 20251017 完成\n",
"任务 20251016 完成\n",
"任务 20251015 完成\n",
"任务 20251014 完成\n",
"任务 20251013 完成\n",
"任务 20251010 完成\n",
"任务 20251009 完成\n",
"任务 20250930 完成\n",
"任务 20250929 完成\n"
]
}
],

236
main/data/update/update_daily_basic.ipynb
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@@ -94,17 +94,17 @@
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 8674588 entries, 0 to 26945\n",
"Index: 9155905 entries, 0 to 27115\n",
"Data columns (total 2 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
" 0 ts_code object\n",
" 1 trade_date object\n",
"dtypes: object(2)\n",
"memory usage: 198.5+ MB\n",
"memory usage: 209.6+ MB\n",
"None\n",
"20250523\n",
"20250526\n"
"20250926\n",
"20250929\n"
]
}
],
@@ -121,7 +121,7 @@
" max_date = df['trade_date'].max()\n",
"\n",
"print(max_date)\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250720')\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20251020')\n",
"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
"trade_dates = trade_cal[trade_cal['cal_date'] > max_date]['cal_date'].tolist()\n",
"start_date = min(trade_dates)\n",
@@ -144,45 +144,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"任务 20250718 完成\n",
"任务 20250717 完成\n",
"任务 20250716 完成\n",
"任务 20250715 完成\n",
"任务 20250714 完成\n",
"任务 20250711 完成\n",
"任务 20250709 完成\n",
"任务 20250710 完成\n",
"任务 20250708 完成\n",
"任务 20250707 完成\n",
"任务 20250704 完成\n",
"任务 20250703 完成\n",
"任务 20250702 完成\n",
"任务 20250701 完成\n",
"任务 20250630 完成\n",
"任务 20250627 完成\n",
"任务 20250626 完成\n",
"任务 20250625 完成\n",
"任务 20250624 完成\n",
"任务 20250623 完成\n",
"任务 20250620 完成\n",
"任务 20250619 完成\n",
"任务 20250618 完成\n",
"任务 20250617 完成\n",
"任务 20250616 完成\n",
"任务 20250613 完成\n",
"任务 20250612 完成\n",
"任务 20250611 完成\n",
"任务 20250610 完成\n",
"任务 20250609 完成\n",
"任务 20250606 完成\n",
"任务 20250605 完成\n",
"任务 20250603 完成\n",
"任务 20250604 完成\n",
"任务 20250530 完成\n",
"任务 20250529 完成\n",
"任务 20250528 完成\n",
"任务 20250527 完成\n",
"任务 20250526 完成\n"
"任务 20251017 完成\n",
"任务 20251020 完成\n",
"任务 20251015 完成\n",
"任务 20251016 完成\n",
"任务 20251014 完成\n",
"任务 20251013 完成\n",
"任务 20251010 完成\n",
"任务 20251009 完成\n",
"任务 20250930 完成\n",
"任务 20250929 完成\n"
]
}
],
@@ -253,58 +224,58 @@
"output_type": "stream",
"text": [
" ts_code trade_date close turnover_rate turnover_rate_f \\\n",
"0 603990.SH 20250530 14.96 3.7919 4.9168 \n",
"1 603666.SH 20250530 33.72 2.4954 4.7137 \n",
"2 001339.SZ 20250530 45.78 7.0710 7.0710 \n",
"3 002006.SZ 20250530 16.67 2.4368 3.4806 \n",
"4 603353.SH 20250530 15.21 1.3567 4.1316 \n",
"0 600642.SH 20251010 8.03 0.4806 1.3835 \n",
"1 600295.SH 20251010 10.76 0.8549 3.7056 \n",
"2 600444.SH 20251010 19.00 9.6611 17.4605 \n",
"3 605100.SH 20251010 28.72 3.4770 7.6902 \n",
"4 301399.SZ 20251010 19.53 3.9562 4.6772 \n",
"... ... ... ... ... ... \n",
"26918 002670.SZ 20250526 11.86 0.7662 2.3092 \n",
"26919 839946.BJ 20250526 9.67 4.8520 6.8863 \n",
"26920 688076.SH 20250526 49.59 5.9483 9.5054 \n",
"26921 300519.SZ 20250526 14.44 2.4601 3.8976 \n",
"26922 300468.SZ 20250526 18.15 6.8275 8.8410 \n",
"21679 600653.SH 20250929 2.13 2.1746 2.9589 \n",
"21680 002344.SZ 20250929 4.49 1.7080 3.6338 \n",
"21681 301162.SZ 20250929 60.30 2.8491 3.5744 \n",
"21682 920077.BJ 20250929 14.43 1.1113 1.6410 \n",
"21683 300283.SZ 20250929 7.04 4.8583 5.7018 \n",
"\n",
" volume_ratio pe pe_ttm pb ps ps_ttm \\\n",
"0 0.65 NaN NaN 5.5665 9.8735 11.0137 \n",
"1 1.15 NaN NaN 3.2133 11.8990 10.3525 \n",
"2 1.22 91.7742 74.3709 5.3909 2.8419 2.7478 \n",
"3 0.81 58.9666 65.5384 3.6508 5.0124 5.4591 \n",
"4 1.10 90.1163 80.8019 1.5917 0.9380 0.9517 \n",
"... ... ... ... ... ... ... \n",
"26918 0.75 137.0866 106.8454 2.0610 15093.0115 14821.3328 \n",
"26919 0.55 NaN NaN 5.7695 2.5489 2.4978 \n",
"26920 3.15 27.5757 22.7263 3.7628 6.8632 6.0784 \n",
"26921 1.14 45.8504 44.3443 2.7022 8.6318 8.8737 \n",
"26922 1.08 142.9746 150.8960 5.8350 13.0086 13.6702 \n",
" volume_ratio pe pe_ttm pb ps ps_ttm dv_ratio \\\n",
"0 1.49 9.9635 10.2617 1.1073 1.3268 1.3600 4.9816 \n",
"1 1.56 16.3053 16.4683 1.4839 1.0603 1.1230 7.4349 \n",
"2 2.84 69.2746 55.7147 3.8398 3.6313 3.5392 0.5263 \n",
"3 0.55 66.7896 123.2961 2.7276 5.3634 6.7180 2.0794 \n",
"4 0.94 60.7990 75.8958 2.7675 6.8812 7.1828 1.2177 \n",
"... ... ... ... ... ... ... ... \n",
"21679 0.72 107.4073 227.6354 5.4498 0.9887 0.9724 0.0000 \n",
"21680 0.70 64.8238 75.9239 0.6834 5.5516 5.5560 0.9577 \n",
"21681 0.96 85.4251 76.2427 5.3380 14.5424 12.3677 0.5586 \n",
"21682 0.51 90.3399 82.4861 3.3572 5.2895 4.1636 NaN \n",
"21683 0.94 NaN NaN 3.2821 1.1161 0.9970 0.2499 \n",
"\n",
" dv_ratio dv_ttm total_share float_share free_share total_mv \\\n",
"0 0.0000 NaN 30628.2731 30628.2731 23620.5583 4.581990e+05 \n",
"1 0.0000 NaN 20649.0816 20649.0816 10931.3716 6.962870e+05 \n",
"2 0.2622 0.3498 25042.9670 7313.0995 7313.0995 1.146467e+06 \n",
"3 0.7749 0.7749 51979.3440 45516.0000 31865.7600 8.664957e+05 \n",
"4 0.6462 1.3036 17339.4000 17041.8000 5596.0000 2.637323e+05 \n",
"... ... ... ... ... ... ... \n",
"26918 0.0000 NaN 193508.4653 162335.0634 53860.6790 2.295010e+06 \n",
"26919 NaN NaN 13499.0443 9702.8595 6836.5574 1.305358e+05 \n",
"26920 NaN NaN 22487.0915 22487.0915 14071.9565 1.115135e+06 \n",
"26921 2.7701 2.7701 16000.0000 11410.0000 7201.9100 2.310400e+05 \n",
"26922 0.3306 0.3306 53064.9275 52979.4065 40913.5262 9.631284e+05 \n",
" dv_ttm total_share float_share free_share total_mv \\\n",
"0 5.6040 489407.9376 489381.3156 170006.8520 3.929946e+06 \n",
"1 5.5762 279877.6254 197557.6254 45577.9458 3.011483e+06 \n",
"2 0.5789 14642.1932 14642.1932 8101.7360 2.782017e+05 \n",
"3 1.0446 17113.2000 16993.2000 7683.2000 4.914911e+05 \n",
"4 1.0594 18502.0000 5468.3586 4625.5000 3.613441e+05 \n",
"... ... ... ... ... ... \n",
"21679 NaN 194638.0317 194638.0317 143048.5612 4.145790e+05 \n",
"21680 0.8463 128261.6960 128145.0092 60233.0025 5.758950e+05 \n",
"21681 0.9704 13258.3724 8522.5548 6793.1764 7.994799e+05 \n",
"21682 NaN 58768.1817 31695.6817 21464.7599 8.480249e+05 \n",
"21683 NaN 49697.8222 36721.8502 31289.2680 3.498727e+05 \n",
"\n",
" circ_mv is_st \n",
"0 4.581990e+05 False \n",
"1 6.962870e+05 False \n",
"2 3.347937e+05 False \n",
"3 7.587517e+05 False \n",
"4 2.592058e+05 False \n",
"0 3.929732e+06 False \n",
"1 2.125720e+06 False \n",
"2 2.782017e+05 False \n",
"3 4.880447e+05 False \n",
"4 1.067970e+05 False \n",
"... ... ... \n",
"26918 1.925294e+06 False \n",
"26919 9.382665e+04 False \n",
"26920 1.115135e+06 False \n",
"26921 1.647604e+05 False \n",
"26922 9.615762e+05 False \n",
"21679 4.145790e+05 False \n",
"21680 5.753711e+05 False \n",
"21681 5.139101e+05 False \n",
"21682 4.573687e+05 False \n",
"21683 2.585218e+05 False \n",
"\n",
"[26923 rows x 19 columns]\n"
"[21684 rows x 19 columns]\n"
]
}
],
@@ -329,58 +300,45 @@
"output_type": "stream",
"text": [
" ts_code trade_date close turnover_rate turnover_rate_f \\\n",
"16 300536.SZ 20250530 8.67 2.8854 3.5632 \n",
"78 000668.SZ 20250530 7.94 4.1498 7.0226 \n",
"112 002231.SZ 20250530 3.28 8.9944 10.0552 \n",
"147 300313.SZ 20250530 6.28 6.0110 12.4720 \n",
"158 603838.SH 20250530 5.73 0.9777 2.6542 \n",
"9 300313.SZ 20251010 8.84 3.1146 6.4625 \n",
"20 603838.SH 20251010 7.80 0.5503 1.5146 \n",
"29 603813.SH 20251010 24.06 1.5835 4.5173 \n",
"48 002742.SZ 20251010 4.65 1.0473 1.2924 \n",
"69 603559.SH 20251010 8.50 0.2072 0.2945 \n",
"... ... ... ... ... ... \n",
"26733 603828.SH 20250526 4.98 0.9734 1.9562 \n",
"26751 600599.SH 20250526 7.46 2.5125 6.3118 \n",
"26785 000820.SZ 20250526 3.02 13.6997 14.0750 \n",
"26885 002005.SZ 20250526 1.77 0.3214 0.5145 \n",
"26905 603869.SH 20250526 6.15 0.3000 0.7946 \n",
"21466 603021.SH 20250929 4.62 1.3860 2.3418 \n",
"21552 300020.SZ 20250929 3.58 1.5031 1.6828 \n",
"21554 000506.SZ 20250929 10.88 10.5560 15.7565 \n",
"21603 600636.SH 20250929 8.29 0.4693 0.7963 \n",
"21661 603843.SH 20250929 5.17 0.3798 0.5364 \n",
"\n",
" volume_ratio pe pe_ttm pb ps ps_ttm dv_ratio \\\n",
"16 0.55 NaN NaN 4.9112 10.9775 12.1174 0.0 \n",
"78 1.07 NaN NaN 1.6212 8.7361 5.6924 0.0 \n",
"112 0.74 NaN NaN 4.3227 3.9056 5.3690 0.0 \n",
"147 0.92 NaN NaN NaN 14.2840 13.5826 0.0 \n",
"158 1.06 NaN NaN 1.9039 6.4291 5.8279 0.0 \n",
"... ... ... ... ... ... ... ... \n",
"26733 0.56 345.783 1670.8958 3.9261 1.2065 1.3013 0.0 \n",
"26751 0.68 NaN NaN 11.2319 3.8238 3.9211 0.0 \n",
"26785 2.40 NaN NaN 12.4588 15.8309 20.1399 0.0 \n",
"26885 0.48 NaN NaN 15.9120 4.2066 4.2221 0.0 \n",
"26905 1.00 149.594 167.2545 0.8344 4.6640 5.0668 0.0 \n",
" volume_ratio pe pe_ttm pb ps ps_ttm dv_ratio dv_ttm \\\n",
"9 1.30 NaN NaN NaN 20.1067 20.9731 0.0000 NaN \n",
"20 0.57 NaN NaN 2.6121 8.7517 6.9304 0.0000 NaN \n",
"29 1.88 NaN NaN 4.5222 8.4776 7.5124 1.0313 NaN \n",
"48 1.28 NaN NaN NaN 1.6800 2.1226 0.0000 NaN \n",
"69 0.60 NaN NaN 3.5043 9.5964 8.2315 0.0000 NaN \n",
"... ... .. ... ... ... ... ... ... \n",
"21466 0.80 NaN NaN NaN 3.5891 3.7851 0.0000 NaN \n",
"21552 1.00 NaN NaN 0.9812 5.1924 18.4036 0.0000 NaN \n",
"21554 3.17 NaN NaN 16.4257 30.3341 23.4860 0.0000 NaN \n",
"21603 0.81 NaN NaN 1.7909 12.8512 11.0116 0.4825 0.6031 \n",
"21661 0.05 NaN NaN 12.5612 2.6558 3.1369 0.0000 NaN \n",
"\n",
" dv_ttm total_share float_share free_share total_mv \\\n",
"16 NaN 29328.8133 29325.3240 23747.3240 254280.8113 \n",
"78 NaN 14684.1890 14684.1890 8677.2104 116592.4607 \n",
"112 NaN 34685.0017 29481.8767 26371.6067 113766.8056 \n",
"147 NaN 31297.7396 19735.2789 9511.5479 196549.8047 \n",
"158 NaN 32001.6000 32001.6000 11788.1468 183369.1680 \n",
"... ... ... ... ... ... \n",
"26733 NaN 59596.0158 59593.9625 29654.2988 296788.1587 \n",
"26751 NaN 16600.0000 16600.0000 6607.7948 123836.0000 \n",
"26785 NaN 64655.5179 29696.6877 28904.9696 195259.6641 \n",
"26885 NaN 175242.4858 175199.3158 109452.0915 310179.1999 \n",
"26905 NaN 50450.0508 50450.0508 19045.9689 310267.8124 \n",
" total_share float_share free_share total_mv circ_mv is_st \n",
"9 31297.7396 19735.2789 9511.5479 2.766720e+05 1.744599e+05 True \n",
"20 32001.6000 32001.6000 11627.0468 2.496125e+05 2.496125e+05 True \n",
"29 10501.5000 10501.5000 3681.2000 2.526661e+05 2.526661e+05 True \n",
"48 43200.0000 43185.8082 34994.8239 2.008800e+05 2.008140e+05 True \n",
"69 40127.6979 40127.6979 28231.9697 3.410854e+05 3.410854e+05 True \n",
"... ... ... ... ... ... ... \n",
"21466 31994.8070 31994.8070 18936.7934 1.478160e+05 1.478160e+05 True \n",
"21552 79467.7974 76663.9584 68475.6577 2.844947e+05 2.744570e+05 True \n",
"21554 92901.7761 92858.4361 62210.1427 1.010771e+06 1.010300e+06 True \n",
"21603 43863.6802 43863.6802 25849.6552 3.636299e+05 3.636299e+05 True \n",
"21661 69962.3237 69962.3237 49541.4702 3.617052e+05 3.617052e+05 True \n",
"\n",
" circ_mv is_st \n",
"16 254250.5591 True \n",
"78 116592.4607 True \n",
"112 96700.5556 True \n",
"147 123937.5515 True \n",
"158 183369.1680 True \n",
"... ... ... \n",
"26733 296777.9333 True \n",
"26751 123836.0000 True \n",
"26785 89683.9969 True \n",
"26885 310102.7890 True \n",
"26905 310267.8124 True \n",
"\n",
"[944 rows x 19 columns]\n"
"[749 rows x 19 columns]\n"
]
}
],
@@ -430,7 +388,7 @@
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 8701511 entries, 0 to 26922\n",
"Index: 9177589 entries, 0 to 21683\n",
"Data columns (total 3 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
@@ -438,7 +396,7 @@
" 1 trade_date object\n",
" 2 is_st bool \n",
"dtypes: bool(1), object(2)\n",
"memory usage: 207.5+ MB\n",
"memory usage: 218.8+ MB\n",
"None\n"
]
}

1258
main/data/update/update_daily_data.ipynb
View File

File diff suppressed because it is too large Load Diff

142
main/data/update/update_money_flow.ipynb
View File

@@ -34,17 +34,17 @@
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 8507431 entries, 0 to 25615\n",
"Index: 8964780 entries, 0 to 25739\n",
"Data columns (total 2 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
" 0 ts_code object\n",
" 1 trade_date object\n",
"dtypes: object(2)\n",
"memory usage: 194.7+ MB\n",
"memory usage: 205.2+ MB\n",
"None\n",
"20250523\n",
"start_date: 20250526\n"
"20250926\n",
"start_date: 20250929\n"
]
}
],
@@ -61,7 +61,7 @@
" max_date = df['trade_date'].max()\n",
"\n",
"print(max_date)\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250720')\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20251020')\n",
"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
"trade_dates = trade_cal[trade_cal['cal_date'] > max_date]['cal_date'].tolist()\n",
"start_date = min(trade_dates)\n",
@@ -84,45 +84,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"任务 20250717 完成\n",
"任务 20250718 完成\n",
"任务 20250715 完成\n",
"任务 20250716 完成\n",
"任务 20250714 完成\n",
"任务 20250711 完成\n",
"任务 20250710 完成\n",
"任务 20250709 完成\n",
"任务 20250708 完成\n",
"任务 20250707 完成\n",
"任务 20250704 完成\n",
"任务 20250703 完成\n",
"任务 20250702 完成\n",
"任务 20250701 完成\n",
"任务 20250630 完成\n",
"任务 20250627 完成\n",
"任务 20250626 完成\n",
"任务 20250625 完成\n",
"任务 20250624 完成\n",
"任务 20250623 完成\n",
"任务 20250620 完成\n",
"任务 20250619 完成\n",
"任务 20250618 完成\n",
"任务 20250617 完成\n",
"任务 20250616 完成\n",
"任务 20250613 完成\n",
"任务 20250612 完成\n",
"任务 20250611 完成\n",
"任务 20250610 完成\n",
"任务 20250609 完成\n",
"任务 20250606 完成\n",
"任务 20250605 完成\n",
"任务 20250604 完成\n",
"任务 20250603 完成\n",
"任务 20250530 完成\n",
"任务 20250529 完成\n",
"任务 20250528 完成\n",
"任务 20250527 完成\n",
"任务 20250526 完成\n"
"任务 20251020 完成\n",
"任务 20251017 完成\n",
"任务 20251016 完成\n",
"任务 20251015 完成\n",
"任务 20251014 完成\n",
"任务 20251013 完成\n",
"任务 20251009 完成\n",
"任务 20251010 完成\n",
"任务 20250929 完成\n",
"任务 20250930 完成\n"
]
}
],
@@ -200,6 +171,89 @@
"\n",
"print(\"所有每日基础数据获取并保存完毕！\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e6f2a2fe",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" ts_code trade_date buy_sm_vol buy_sm_amount sell_sm_vol \\\n",
"0 603290.SH 20251009 45532 52028.67 42778 \n",
"1 600936.SH 20251009 42537 1545.21 42382 \n",
"2 300429.SZ 20251009 81914 11768.07 64063 \n",
"3 300879.SZ 20251009 15330 5366.90 11651 \n",
"4 300031.SZ 20251009 51381 12650.70 43869 \n",
"... ... ... ... ... ... \n",
"20574 688083.SH 20250930 13247 10094.95 11236 \n",
"20575 002939.SZ 20250930 372609 43083.12 232240 \n",
"20576 688303.SH 20250930 62478 18094.19 55086 \n",
"20577 300146.SZ 20250930 50078 5792.85 35214 \n",
"20578 688351.SH 20250930 15096 3333.84 14017 \n",
"\n",
" sell_sm_amount buy_md_vol buy_md_amount sell_md_vol sell_md_amount \\\n",
"0 48942.98 53824 61495.85 54076 61851.39 \n",
"1 1538.97 24175 878.06 31948 1160.07 \n",
"2 9211.49 88583 12730.36 88244 12682.05 \n",
"3 4089.33 15591 5464.12 17057 5976.94 \n",
"4 10822.65 56173 13836.60 49423 12190.63 \n",
"... ... ... ... ... ... \n",
"20574 8561.02 10482 7994.12 9858 7514.37 \n",
"20575 26867.01 279904 32371.96 324997 37595.57 \n",
"20576 15952.67 55867 16177.83 53776 15573.61 \n",
"20577 4076.10 46159 5337.00 39420 4560.91 \n",
"20578 3095.89 6482 1430.69 6675 1474.59 \n",
"\n",
" buy_lg_vol buy_lg_amount sell_lg_vol sell_lg_amount buy_elg_vol \\\n",
"0 36150 41253.53 36789 41932.43 10514 \n",
"1 11158 405.04 9212 334.60 5672 \n",
"2 64282 9239.06 72904 10475.38 8221 \n",
"3 10167 3562.24 12327 4313.59 3221 \n",
"4 40306 9938.01 41035 10103.23 6112 \n",
"... ... ... ... ... ... \n",
"20574 6674 5082.80 8224 6273.43 3329 \n",
"20575 204229 23631.31 285167 32986.98 132696 \n",
"20576 33304 9638.04 34809 10074.64 5032 \n",
"20577 47161 5454.07 36321 4202.88 8662 \n",
"20578 2513 555.48 3398 749.54 0 \n",
"\n",
" buy_elg_amount sell_elg_vol sell_elg_amount net_mf_vol \\\n",
"0 12073.88 12377 14125.13 20027 \n",
"1 205.33 0 0.00 -21182 \n",
"2 1183.11 17790 2551.67 -840 \n",
"3 1133.90 3275 1147.29 -4996 \n",
"4 1507.28 19645 4816.08 1531 \n",
"... ... ... ... ... \n",
"20574 2538.01 4413 3361.05 7612 \n",
"20575 15366.29 147033 17003.12 84949 \n",
"20576 1459.24 13010 3768.39 15188 \n",
"20577 1000.95 41105 4744.98 -16754 \n",
"20578 0.00 0 0.00 3406 \n",
"\n",
" net_mf_amount \n",
"0 22734.35 \n",
"1 -766.75 \n",
"2 -90.83 \n",
"3 -1741.72 \n",
"4 385.00 \n",
"... ... \n",
"20574 5816.07 \n",
"20575 9927.60 \n",
"20576 4417.72 \n",
"20577 -1928.39 \n",
"20578 752.20 \n",
"\n",
"[20579 rows x 20 columns]\n"
]
}
],
"source": [
"print(all_daily_data_df)"
]
}
],
"metadata": {

310
main/data/update/update_stk_limit.ipynb
View File

@@ -34,23 +34,23 @@
"output_type": "stream",
"text": [
" ts_code trade_date\n",
"2365 300067.SZ 20250509\n",
"2364 300066.SZ 20250509\n",
"2363 300065.SZ 20250509\n",
"2374 300076.SZ 20250509\n",
"7113 920819.BJ 20250509\n",
"4872 600206.SH 20250926\n",
"4873 600207.SH 20250926\n",
"4874 600208.SH 20250926\n",
"4876 600211.SH 20250926\n",
"7280 920037.BJ 20250926\n",
"<class 'pandas.core.frame.DataFrame'>\n",
"Index: 10457633 entries, 0 to 7113\n",
"Index: 11170571 entries, 0 to 36462\n",
"Data columns (total 2 columns):\n",
" # Column Dtype \n",
"--- ------ ----- \n",
" 0 ts_code object\n",
" 1 trade_date object\n",
"dtypes: object(2)\n",
"memory usage: 239.4+ MB\n",
"memory usage: 255.7+ MB\n",
"None\n",
"20250509\n",
"20250512\n"
"20250926\n",
"20250929\n"
]
}
],
@@ -68,7 +68,7 @@
" max_date = df['trade_date'].max()\n",
"\n",
"print(max_date)\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20250720')\n",
"trade_cal = pro.trade_cal(exchange='', start_date='20170101', end_date='20251020')\n",
"trade_cal = trade_cal[trade_cal['is_open'] == 1] # 只保留交易日\n",
"trade_dates = trade_cal[trade_cal['cal_date'] > max_date]['cal_date'].tolist()\n",
"start_date = min(trade_dates)\n",
@@ -91,55 +91,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
"任务 20250717 完成\n",
"任务 20250718 完成\n",
"任务 20250716 完成\n",
"任务 20250715 完成\n",
"任务 20250714 完成\n",
"任务 20250711 完成\n",
"任务 20250710 完成\n",
"任务 20250709 完成\n",
"任务 20250707 完成\n",
"任务 20250708 完成\n",
"任务 20250704 完成\n",
"任务 20250703 完成\n",
"任务 20250702 完成\n",
"任务 20250701 完成\n",
"任务 20250627 完成\n",
"任务 20250630 完成\n",
"任务 20250626 完成\n",
"任务 20250625 完成\n",
"任务 20250624 完成\n",
"任务 20250623 完成\n",
"任务 20250620 完成\n",
"任务 20250619 完成\n",
"任务 20250617 完成\n",
"任务 20250618 完成\n",
"任务 20250613 完成\n",
"任务 20250616 完成\n",
"任务 20250612 完成\n",
"任务 20250611 完成\n",
"任务 20250610 完成\n",
"任务 20250609 完成\n",
"任务 20250606 完成\n",
"任务 20250605 完成\n",
"任务 20250604 完成\n",
"任务 20250603 完成\n",
"任务 20250530 完成\n",
"任务 20250529 完成\n",
"任务 20250528 完成\n",
"任务 20250527 完成\n",
"任务 20250526 完成\n",
"任务 20250523 完成\n",
"任务 20250521 完成\n",
"任务 20250522 完成\n",
"任务 20250519 完成\n",
"任务 20250520 完成\n",
"任务 20250516 完成\n",
"任务 20250515 完成\n",
"任务 20250514 完成\n",
"任务 20250513 完成\n",
"任务 20250512 完成\n"
"任务 20251020 完成\n",
"任务 20251017 完成\n",
"任务 20251015 完成\n",
"任务 20251016 完成\n",
"任务 20251013 完成\n",
"任务 20251014 完成\n",
"任务 20251010 完成\n",
"任务 20251009 完成\n",
"任务 20250929 完成\n",
"任务 20250930 完成\n"
]
}
],
@@ -191,201 +152,58 @@
"output_type": "stream",
"text": [
"[ trade_date ts_code up_limit down_limit\n",
"0 20250530 000001.SZ 12.61 10.31\n",
"1 20250530 000002.SZ 7.37 6.03\n",
"2 20250530 000004.SZ 10.38 9.40\n",
"3 20250530 000006.SZ 7.69 6.29\n",
"4 20250530 000007.SZ 8.61 7.05\n",
"0 20251010 000001.SZ 12.54 10.26\n",
"1 20251010 000002.SZ 7.47 6.11\n",
"2 20251010 000004.SZ 12.26 11.10\n",
"3 20251010 000006.SZ 11.94 9.77\n",
"4 20251010 000007.SZ 8.12 6.64\n",
"... ... ... ... ...\n",
"7136 20250530 920445.BJ 13.61 7.33\n",
"7137 20250530 920489.BJ 32.64 17.58\n",
"7138 20250530 920682.BJ 13.81 7.45\n",
"7139 20250530 920799.BJ 78.92 42.50\n",
"7140 20250530 920819.BJ 5.90 3.18\n",
"7309 20251010 920978.BJ 50.08 26.98\n",
"7310 20251010 920981.BJ 48.04 25.88\n",
"7311 20251010 920982.BJ 354.64 190.96\n",
"7312 20251010 920985.BJ 11.86 6.40\n",
"7313 20251010 920992.BJ 27.87 15.01\n",
"\n",
"[7141 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250529 000001.SZ 12.68 10.38\n",
"1 20250529 000002.SZ 7.35 6.01\n",
"2 20250529 000004.SZ 10.44 9.44\n",
"3 20250529 000006.SZ 7.78 6.36\n",
"4 20250529 000007.SZ 8.48 6.94\n",
"[7314 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20251009 000001.SZ 12.47 10.21\n",
"1 20251009 000002.SZ 7.58 6.20\n",
"2 20251009 000004.SZ 11.68 10.56\n",
"3 20251009 000006.SZ 11.32 9.26\n",
"4 20251009 000007.SZ 8.02 6.56\n",
"... ... ... ... ...\n",
"7132 20250529 920445.BJ 13.28 7.16\n",
"7133 20250529 920489.BJ 31.73 17.09\n",
"7134 20250529 920682.BJ 13.55 7.31\n",
"7135 20250529 920799.BJ 73.17 39.41\n",
"7136 20250529 920819.BJ 5.86 3.16\n",
"7306 20251009 920978.BJ 50.44 27.16\n",
"7307 20251009 920981.BJ 48.11 25.91\n",
"7308 20251009 920982.BJ 366.06 197.12\n",
"7309 20251009 920985.BJ 12.01 6.47\n",
"7310 20251009 920992.BJ 27.39 14.75\n",
"\n",
"[7137 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250528 000001.SZ 12.64 10.34\n",
"1 20250528 000002.SZ 7.34 6.00\n",
"2 20250528 000004.SZ 10.52 9.52\n",
"3 20250528 000006.SZ 7.96 6.52\n",
"4 20250528 000007.SZ 8.51 6.97\n",
"[7311 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250929 000001.SZ 12.54 10.26\n",
"1 20250929 000002.SZ 7.48 6.12\n",
"2 20250929 000004.SZ 11.00 9.96\n",
"3 20250929 000006.SZ 10.46 8.56\n",
"4 20250929 000007.SZ 7.63 6.25\n",
"... ... ... ... ...\n",
"7130 20250528 920445.BJ 13.50 7.28\n",
"7131 20250528 920489.BJ 32.70 17.62\n",
"7132 20250528 920682.BJ 13.71 7.39\n",
"7133 20250528 920799.BJ 73.60 39.64\n",
"7134 20250528 920819.BJ 5.87 3.17\n",
"7302 20250929 920445.BJ 14.37 7.75\n",
"7303 20250929 920489.BJ 29.34 15.80\n",
"7304 20250929 920682.BJ 13.10 7.06\n",
"7305 20250929 920799.BJ 70.78 38.12\n",
"7306 20250929 920819.BJ 5.52 2.98\n",
"\n",
"[7135 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250527 000001.SZ 12.56 10.28\n",
"1 20250527 000002.SZ 7.29 5.97\n",
"2 20250527 000004.SZ 10.02 9.06\n",
"3 20250527 000006.SZ 7.58 6.20\n",
"4 20250527 000007.SZ 8.37 6.85\n",
"[7307 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250930 000001.SZ 12.51 10.23\n",
"1 20250930 000002.SZ 7.49 6.13\n",
"2 20250930 000004.SZ 11.12 10.06\n",
"3 20250930 000006.SZ 10.29 8.42\n",
"4 20250930 000007.SZ 7.92 6.48\n",
"... ... ... ... ...\n",
"7128 20250527 920445.BJ 13.28 7.16\n",
"7129 20250527 920489.BJ 33.96 18.30\n",
"7130 20250527 920682.BJ 13.59 7.33\n",
"7131 20250527 920799.BJ 73.38 39.52\n",
"7132 20250527 920819.BJ 5.55 2.99\n",
"7305 20250930 920445.BJ 14.67 7.91\n",
"7306 20250930 920489.BJ 29.26 15.76\n",
"7307 20250930 920682.BJ 12.92 6.96\n",
"7308 20250930 920799.BJ 73.19 39.41\n",
"7309 20250930 920819.BJ 5.55 2.99\n",
"\n",
"[7133 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250526 000001.SZ 12.61 10.31\n",
"1 20250526 000002.SZ 7.29 5.97\n",
"2 20250526 000004.SZ 9.54 8.64\n",
"3 20250526 000006.SZ 7.44 6.08\n",
"4 20250526 000007.SZ 8.66 7.08\n",
"... ... ... ... ...\n",
"7130 20250526 920445.BJ 12.88 6.94\n",
"7131 20250526 920489.BJ 31.96 17.22\n",
"7132 20250526 920682.BJ 12.77 6.89\n",
"7133 20250526 920799.BJ 72.35 38.97\n",
"7134 20250526 920819.BJ 5.48 2.96\n",
"\n",
"[7135 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250523 000001.SZ 12.71 10.40\n",
"1 20250523 000002.SZ 7.34 6.00\n",
"2 20250523 000004.SZ 9.87 8.93\n",
"3 20250523 000006.SZ 7.54 6.17\n",
"4 20250523 000007.SZ 8.80 7.20\n",
"... ... ... ... ...\n",
"7130 20250523 920445.BJ 13.01 7.01\n",
"7131 20250523 920489.BJ 30.58 16.48\n",
"7132 20250523 920682.BJ 12.83 6.91\n",
"7133 20250523 920799.BJ 74.10 39.90\n",
"7134 20250523 920819.BJ 5.56 3.00\n",
"\n",
"[7135 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250521 000001.SZ 12.53 10.25\n",
"1 20250521 000002.SZ 7.46 6.10\n",
"2 20250521 000004.SZ 9.47 8.57\n",
"3 20250521 000006.SZ 7.61 6.23\n",
"4 20250521 000007.SZ 8.28 6.78\n",
"... ... ... ... ...\n",
"7129 20250521 920445.BJ 14.02 7.56\n",
"7130 20250521 920489.BJ 32.89 17.71\n",
"7131 20250521 920682.BJ 13.83 7.45\n",
"7132 20250521 920799.BJ 77.87 41.93\n",
"7133 20250521 920819.BJ 5.95 3.21\n",
"\n",
"[7134 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250522 000001.SZ 12.63 10.33\n",
"1 20250522 000002.SZ 7.44 6.08\n",
"2 20250522 000004.SZ 9.94 9.00\n",
"3 20250522 000006.SZ 7.43 6.08\n",
"4 20250522 000007.SZ 8.43 6.89\n",
"... ... ... ... ...\n",
"7130 20250522 920445.BJ 13.68 7.38\n",
"7131 20250522 920489.BJ 32.95 17.75\n",
"7132 20250522 920682.BJ 13.41 7.23\n",
"7133 20250522 920799.BJ 77.42 41.70\n",
"7134 20250522 920819.BJ 5.81 3.13\n",
"\n",
"[7135 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250519 000001.SZ 12.52 10.24\n",
"1 20250519 000002.SZ 7.45 6.09\n",
"2 20250519 000004.SZ 8.68 7.86\n",
"3 20250519 000006.SZ 7.17 5.87\n",
"4 20250519 000007.SZ 8.05 6.59\n",
"... ... ... ... ...\n",
"7128 20250519 920445.BJ 13.96 7.52\n",
"7129 20250519 920489.BJ 30.29 16.31\n",
"7130 20250519 920682.BJ 13.35 7.19\n",
"7131 20250519 920799.BJ 77.87 41.93\n",
"7132 20250519 920819.BJ 5.91 3.19\n",
"\n",
"[7133 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250520 000001.SZ 12.51 10.23\n",
"1 20250520 000002.SZ 7.48 6.12\n",
"2 20250520 000004.SZ 9.02 8.16\n",
"3 20250520 000006.SZ 7.66 6.26\n",
"4 20250520 000007.SZ 8.18 6.70\n",
"... ... ... ... ...\n",
"7128 20250520 920445.BJ 13.97 7.53\n",
"7129 20250520 920489.BJ 31.75 17.11\n",
"7130 20250520 920682.BJ 13.23 7.13\n",
"7131 20250520 920799.BJ 77.83 41.91\n",
"7132 20250520 920819.BJ 5.86 3.16\n",
"\n",
"[7133 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250516 000001.SZ 12.53 10.25\n",
"1 20250516 000002.SZ 7.47 6.11\n",
"2 20250516 000004.SZ 9.14 8.27\n",
"3 20250516 000006.SZ 7.17 5.87\n",
"4 20250516 000007.SZ 8.03 6.57\n",
"... ... ... ... ...\n",
"7125 20250516 920445.BJ 14.80 7.98\n",
"7126 20250516 920489.BJ 30.31 16.33\n",
"7127 20250516 920682.BJ 13.71 7.39\n",
"7128 20250516 920799.BJ 78.03 42.03\n",
"7129 20250516 920819.BJ 5.74 3.10\n",
"\n",
"[7130 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250515 000001.SZ 12.57 10.29\n",
"1 20250515 000002.SZ 7.58 6.20\n",
"2 20250515 000004.SZ 8.90 8.06\n",
"3 20250515 000006.SZ 7.26 5.94\n",
"4 20250515 000007.SZ 8.01 6.55\n",
"... ... ... ... ...\n",
"7119 20250515 920445.BJ 14.80 7.98\n",
"7120 20250515 920489.BJ 31.12 16.76\n",
"7121 20250515 920682.BJ 16.96 9.14\n",
"7122 20250515 920799.BJ 82.13 44.23\n",
"7123 20250515 920819.BJ 5.59 3.01\n",
"\n",
"[7124 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250514 000001.SZ 12.42 10.16\n",
"1 20250514 000002.SZ 7.55 6.17\n",
"2 20250514 000004.SZ 8.96 8.10\n",
"3 20250514 000006.SZ 7.14 5.84\n",
"4 20250514 000007.SZ 8.02 6.56\n",
"... ... ... ... ...\n",
"7117 20250514 920445.BJ 14.04 7.56\n",
"7118 20250514 920489.BJ 31.42 16.92\n",
"7119 20250514 920682.BJ 17.23 9.29\n",
"7120 20250514 920799.BJ 78.22 42.12\n",
"7121 20250514 920819.BJ 5.59 3.01\n",
"\n",
"[7122 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250513 000001.SZ 12.28 10.04\n",
"1 20250513 000002.SZ 7.54 6.17\n",
"2 20250513 000004.SZ 8.53 7.71\n",
"3 20250513 000006.SZ 7.12 5.82\n",
"4 20250513 000007.SZ 7.82 6.40\n",
"... ... ... ... ...\n",
"7116 20250513 920445.BJ 13.36 7.20\n",
"7117 20250513 920489.BJ 31.07 16.73\n",
"7118 20250513 920682.BJ 16.73 9.01\n",
"7119 20250513 920799.BJ 80.47 43.33\n",
"7120 20250513 920819.BJ 5.60 3.02\n",
"\n",
"[7121 rows x 4 columns], trade_date ts_code up_limit down_limit\n",
"0 20250512 000001.SZ 12.27 10.04\n",
"1 20250512 000002.SZ 7.46 6.10\n",
"2 20250512 000004.SZ 8.12 7.34\n",
"3 20250512 000006.SZ 7.08 5.80\n",
"4 20250512 000007.SZ 7.81 6.39\n",
"... ... ... ... ...\n",
"7112 20250512 920445.BJ 13.19 7.11\n",
"7113 20250512 920489.BJ 30.55 16.45\n",
"7114 20250512 920682.BJ 16.34 8.80\n",
"7115 20250512 920799.BJ 78.13 42.07\n",
"7116 20250512 920819.BJ 5.57 3.01\n",
"\n",
"[7117 rows x 4 columns]]\n"
"[7310 rows x 4 columns]]\n"
]
}
],