加载中...
AI 原生量化投研平台AI-native quantitative research platform
正在加载…Loading…
页面仍在加载,可以继续等待,或重新加载。The page is still loading. You can keep waiting or reload.
部分页面资源未能加载,请重新加载。Some page resources could not load. Please reload.
设备当前处于离线状态,恢复连接后可以继续等待或重新加载。Your device is offline. Once connected, you can keep waiting or reload.
该表提供了股票市场的未复权日行情数据,包括股票的开高低收、成交量、成交笔数、成交金额、涨跌幅、换手率、涨/跌停价等关键指标。未复权数据表示没有调整过的原始交易数据,这些数据反映了市场的实际成交情况。
本表提供 A 股的未复权日行情,每只股票每个交易日一行,包含开盘价、最高价、最低价、收盘价、成交量、成交额、成交笔数、涨跌幅、换手率、涨跌停价和累计后复权因子。未复权价格是交易所公布的原始成交价格。需要后复权价格时使用 cn_stock_bar1d。
| 关键字 | 释意 |
|---|---|
| date | 交易日,不含时分秒 |
| instrument | 股票代码,格式为 代码.交易所后缀,如 000001.SZ、600000.SH、920000.BJ |
| 字段 | 口径 |
|---|---|
| name | 证券简称 |
| adjust_factor | 累计后复权因子,与未复权价格相乘得到后复权价格 |
| pre_close / open / high / low / close | 未复权的前收盘价、开盘价、最高价、最低价、收盘价 |
| volume | 成交量,单位为股,是当日累计值 |
| deal_number | 成交笔数 |
| amount | 成交额,单位为元,是当日累计值 |
| change_ratio | 涨跌幅,以小数表示,0.01 表示 1%,等于 close / pre_close - 1 |
| turn | 换手率,以小数表示,0.05 表示 5%,按流通 A 股股本计算 |
| upper_limit / lower_limit | 未复权的涨停价和跌停价,与 cn_stock_limit_price 同一天的取值一致 |
后复权价格按下式计算:
后复权价格 = 未复权价格 * adjust_factor停牌或当日没有成交的股票仍保留一行:open、high、low、close、amount 为空,volume、deal_number、change_ratio、turn 为 0,pre_close、upper_limit、lower_limit 保留。
upper_limit 为 999999.99,lower_limit 为 0.01,例如新股上市首日。这两个值是占位值,不是真实价格,做涨跌停判断时需要排除。2005 年至 2018 年每年有 1.4 万至 9.5 万行取占位值,2019 年起每年 300 至 4800 行。change_ratio 不受涨跌停幅度约束,例如 301718.SZ 在 2026-10-22 为 1.715402。close 为空的行:2005 年至 2018 年每年有 1.4 万至 9.5 万行,2019 年起每年 2000 至 6100 行,2026-10-22 有 5 行。deal_number 前需要先过滤。取 2026-10-28 至 2026-11-04 的数据,按 date、instrument 排序,展示前 5 行和后 5 行。
| date | instrument | name | adjust_factor | pre_close | open | close | high | low | volume | deal_number | amount | change_ratio | turn | upper_limit | lower_limit |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-10-28 00:00:00 | 000001.SZ | 平安银行 | 142.07 | 11.47 | 11.43 | 11.31 | 11.5 | 11.22 | 168700927 | 135235 | 1.91155e+09 | -0.0139494 | 0.00869338 | 12.62 | 10.32 |
| 2026-10-28 00:00:00 | 000002.SZ | 万 科A | 181.704 | 3.3 | 3.32 | 3.29 | 3.33 | 3.26 | 181580769 | 62799 | 5.97382e+08 | -0.0030303 | 0.0186905 | 3.63 | 2.97 |
| 2026-10-28 00:00:00 | 000006.SZ | 深振业A | 39.7397 | 6.28 | 6.32 | 6.44 | 6.47 | 6.28 | 15849200 | 17691 | 1.01305e+08 | 0.0254777 | 0.0117402 | 6.91 | 5.65 |
| 2026-10-28 00:00:00 | 000007.SZ | 全新好 | 8.28353 | 8.9 | 8.88 | 9.08 | 9.22 | 8.88 | 7086100 | 10660 | 6.41093e+07 | 0.0202247 | 0.0204536 | 9.79 | 8.01 |
| 2026-10-28 00:00:00 | 000008.SZ | 神州高铁 | 22.4083 | 2.27 | 2.28 | 2.27 | 2.29 | 2.25 | 14153200 | 9642 | 3.21067e+07 | 0 | 0.00521048 | 2.5 | 2.04 |
| 2026-11-04 00:00:00 | 920978.BJ | 开特股份 | 1.3011 | 17.03 | 17.01 | 17.42 | 17.52 | 16.65 | 2269073 | 0 | 3.86057e+07 | 0.0229008 | 0.0223229 | 22.13 | 11.93 |
| 2026-11-04 00:00:00 | 920981.BJ | 晶赛科技 | 1.43427 | 23.38 | 23.45 | 24.38 | 24.51 | 23.06 | 1670660 | 0 | 3.98263e+07 | 0.0427716 | 0.0434359 | 30.39 | 16.37 |
| 2026-11-04 00:00:00 | 920982.BJ | 锦波生物 | 4.29828 | 139.65 | 139.03 | 138.7 | 142.99 | 135 | 1635806 | 0 | 2.24389e+08 | -0.00680272 | 0.0294925 | 181.54 | 97.76 |
| 2026-11-04 00:00:00 | 920985.BJ | 海泰新能 | 1.62804 | 4.28 | 4.26 | 4.53 | 4.68 | 4.19 | 7579026 | 0 | 3.36572e+07 | 0.0584112 | 0.0345573 | 5.56 | 3 |
| 2026-11-04 00:00:00 | 920992.BJ | 中科美菱 | 1.50266 | 10.48 | 10.44 | 10.56 | 10.69 | 10.31 | 811846 | 0 | 8.5051e+06 | 0.00763359 | 0.0165624 | 13.62 | 7.34 |
import daidf = dai.query(""" SELECT date, instrument, high, low FROM cn_stock_real_bar1d WHERE instrument='000032.SZ' ORDER BY date""", filters={"date": ["2023-01-01", "2023-12-31"]}).df()import daidf = dai.query(""" SELECT date, instrument, t1.open AS real_open, t1.close AS real_close, t2.open AS adjust_open, t2.close AS adjust_close FROM cn_stock_real_bar1d AS t1 JOIN cn_stock_bar1d AS t2 USING (date, instrument) WHERE instrument='000032.SZ' ORDER BY date""", filters={"date": ["2023-01-01", "2023-12-31"]}).df()import daidf = dai.query(""" SELECT instrument, MAX(high) as max_high, MIN(low) as min_low FROM cn_stock_real_bar1d WHERE instrument = '000002.SZ' GROUP BY instrument""", filters={"date": ["2023-01-01", "2023-12-31"]}).df()import daidf = dai.query(""" SELECT instrument, SUM(volume) as total_volume FROM cn_stock_real_bar1d GROUP BY instrument ORDER BY total_volume DESC LIMIT 10""", filters={"date": ["2023-01-01", "2023-12-31"]}).df()import daidf = dai.query(""" SELECT instrument, MAX(change_ratio) as max_change_ratio FROM cn_stock_real_bar1d GROUP BY instrument ORDER BY max_change_ratio DESC LIMIT 5""", filters={"date": ["2023-01-01", "2023-12-31"]}).df()SELECT instrument, name, adjust_factor, pre_close, open, close, high FROM cn_stock_real_bar1d WHERE date >= '2026-10-06' ORDER BY date LIMIT 100
SELECT instrument, name, adjust_factor, pre_close, open, close, high FROM cn_stock_real_bar1d WHERE date >= '2026-10-06' ORDER BY date LIMIT 100