Dataset Viewer
Auto-converted to Parquet Duplicate
symbol
stringclasses
7 values
exchange
stringclasses
2 values
timestamp
timestamp[us]date
2015-01-05 09:30:00
2021-03-31 10:33:00
open
float64
0.63
3.62
high
float64
0.63
3.62
low
float64
0.63
3.62
close
float64
0.63
3.62
volume
int64
0
82M
turnover
float64
0
126M
510050
SH
2015-01-05T09:30:00
2.58
2.58
2.578
2.579
10,885,300
28,084,010
510210
SH
2015-01-05T09:30:00
3.515
3.515
3.515
3.515
0
0
510300
SH
2015-01-05T09:30:00
3.604
3.604
3.604
3.604
11,606,600
41,830,188
510500
SH
2015-01-05T09:30:00
1.505
1.505
1.505
1.505
66,000
99,330
588000
SH
2020-11-16T09:30:00
1.556
1.556
1.556
1.556
20,146,860
31,348,512
159845
SZ
2021-03-31T09:30:00
0.631
0.632
0.631
0.632
272,356
172,152.8
159915
SZ
2015-01-05T09:30:00
1.424
1.424
1.424
1.424
376,900
536,705.6
510050
SH
2015-01-05T09:31:00
2.584
2.59
2.576
2.576
23,471,300
60,587,376
510210
SH
2015-01-05T09:31:00
3.549
3.549
3.549
3.549
500
1,774.5
510300
SH
2015-01-05T09:31:00
3.605
3.609
3.599
3.603
12,762,114
45,994,132
510500
SH
2015-01-05T09:31:00
1.5
1.5
1.495
1.5
57,700
86,546.2
588000
SH
2020-11-16T09:31:00
1.556
1.56
1.462
1.477
81,994,540
125,511,970
159845
SZ
2021-03-31T09:31:00
0.632
0.634
0.632
0.634
406,699
257,043.97
159915
SZ
2015-01-05T09:31:00
1.421
1.425
1.42
1.42
1,342,000
1,906,678.9
510050
SH
2015-01-05T09:32:00
2.577
2.588
2.574
2.58
28,221,900
72,785,530
510210
SH
2015-01-05T09:32:00
3.549
3.549
3.549
3.549
0
0
510300
SH
2015-01-05T09:32:00
3.6
3.606
3.598
3.606
8,936,743
32,199,174
510500
SH
2015-01-05T09:32:00
1.498
1.498
1.492
1.492
148,400
221,811.6
588000
SH
2020-11-16T09:32:00
1.484
1.484
1.465
1.465
42,572,280
62,860,000
159845
SZ
2021-03-31T09:32:00
0.634
0.634
0.632
0.632
65,696
41,536.773
159915
SZ
2015-01-05T09:32:00
1.42
1.42
1.42
1.42
1,062,316
1,508,565.4
510050
SH
2015-01-05T09:33:00
2.588
2.591
2.583
2.585
18,463,900
47,782,516
510210
SH
2015-01-05T09:33:00
3.549
3.549
3.549
3.549
0
0
510300
SH
2015-01-05T09:33:00
3.606
3.608
3.606
3.607
9,077,778
32,740,340
510500
SH
2015-01-05T09:33:00
1.491
1.491
1.49
1.49
50,500
75,259.5
588000
SH
2020-11-16T09:33:00
1.465
1.47
1.464
1.468
29,804,564
43,728,150
159845
SZ
2021-03-31T09:33:00
0.632
0.633
0.632
0.632
232,298
146,825.84
159915
SZ
2015-01-05T09:33:00
1.421
1.421
1.417
1.417
2,148,384
3,049,199
510050
SH
2015-01-05T09:34:00
2.585
2.588
2.585
2.588
21,845,150
56,488,704
510210
SH
2015-01-05T09:34:00
3.549
3.549
3.549
3.549
0
0
510300
SH
2015-01-05T09:34:00
3.609
3.612
3.608
3.611
7,446,392
26,875,494
510500
SH
2015-01-05T09:34:00
1.49
1.49
1.49
1.49
20,000
29,800
588000
SH
2020-11-16T09:34:00
1.468
1.471
1.462
1.462
39,699,584
58,263,224
159845
SZ
2021-03-31T09:34:00
0.632
0.632
0.632
0.632
5,115,834
3,233,210
159915
SZ
2015-01-05T09:34:00
1.418
1.418
1.41
1.41
825,100
1,166,743.1
510050
SH
2015-01-05T09:35:00
2.589
2.593
2.588
2.588
24,600,380
63,684,988
510210
SH
2015-01-05T09:35:00
3.549
3.549
3.549
3.549
0
0
510300
SH
2015-01-05T09:35:00
3.609
3.611
3.609
3.609
11,744,500
42,399,244
510500
SH
2015-01-05T09:35:00
1.491
1.493
1.491
1.493
106,100
158,308.9
588000
SH
2020-11-16T09:35:00
1.462
1.462
1.46
1.462
27,582,508
40,277,596
159845
SZ
2021-03-31T09:35:00
0.632
0.633
0.632
0.632
14,581,600
9,215,591
159915
SZ
2015-01-05T09:35:00
1.411
1.416
1.411
1.416
1,792,915
2,531,820.8
510050
SH
2015-01-05T09:36:00
2.589
2.597
2.589
2.59
23,266,600
60,290,950
510210
SH
2015-01-05T09:36:00
3.549
3.549
3.549
3.549
0
0
510300
SH
2015-01-05T09:36:00
3.61
3.611
3.61
3.611
8,697,548
31,401,206
510500
SH
2015-01-05T09:36:00
1.493
1.493
1.492
1.493
304,100
454,017.8
588000
SH
2020-11-16T09:36:00
1.462
1.469
1.461
1.466
15,930,007
23,355,530
159845
SZ
2021-03-31T09:36:00
0.632
0.633
0.632
0.633
4,253,977
2,689,054
159915
SZ
2015-01-05T09:36:00
1.416
1.416
1.414
1.415
486,600
688,847
510050
SH
2015-01-05T09:37:00
2.591
2.593
2.59
2.59
23,756,100
61,551,190
510210
SH
2015-01-05T09:37:00
3.52
3.52
3.52
3.52
4,600
16,192
510300
SH
2015-01-05T09:37:00
3.61
3.612
3.609
3.609
17,086,296
61,689,764
510500
SH
2015-01-05T09:37:00
1.493
1.495
1.493
1.493
693,361
1,035,272.2
588000
SH
2020-11-16T09:37:00
1.466
1.466
1.456
1.457
28,783,442
42,030,320
159845
SZ
2021-03-31T09:37:00
0.633
0.634
0.633
0.634
2,257,315
1,430,136.1
159915
SZ
2015-01-05T09:37:00
1.415
1.416
1.414
1.414
744,000
1,052,671.5
510050
SH
2015-01-05T09:38:00
2.591
2.591
2.588
2.588
16,915,068
43,812,820
510210
SH
2015-01-05T09:38:00
3.52
3.52
3.52
3.52
0
0
510300
SH
2015-01-05T09:38:00
3.61
3.614
3.608
3.61
15,293,379
55,211,316
510500
SH
2015-01-05T09:38:00
1.496
1.497
1.494
1.494
35,000
52,368
588000
SH
2020-11-16T09:38:00
1.456
1.462
1.456
1.462
13,036,582
19,018,124
159845
SZ
2021-03-31T09:38:00
0.634
0.635
0.634
0.634
1,040,582
659,739
159915
SZ
2015-01-05T09:38:00
1.413
1.414
1.41
1.41
1,200,900
1,695,334.4
510050
SH
2015-01-05T09:39:00
2.588
2.588
2.585
2.586
14,393,600
37,227,090
510210
SH
2015-01-05T09:39:00
3.52
3.52
3.52
3.52
0
0
510300
SH
2015-01-05T09:39:00
3.61
3.614
3.609
3.613
11,090,644
40,069,840
510500
SH
2015-01-05T09:39:00
1.496
1.496
1.494
1.496
47,000
70,252
588000
SH
2020-11-16T09:39:00
1.461
1.461
1.458
1.461
16,296,851
23,786,186
159845
SZ
2021-03-31T09:39:00
0.634
0.634
0.633
0.633
274,660
173,861.98
159915
SZ
2015-01-05T09:39:00
1.41
1.41
1.406
1.407
480,800
677,159
510050
SH
2015-01-05T09:40:00
2.586
2.587
2.585
2.585
11,765,000
30,423,624
510210
SH
2015-01-05T09:40:00
3.52
3.52
3.52
3.52
0
0
510300
SH
2015-01-05T09:40:00
3.613
3.616
3.613
3.613
12,169,044
43,984,064
510500
SH
2015-01-05T09:40:00
1.496
1.496
1.494
1.495
82,700
123,633.9
588000
SH
2020-11-16T09:40:00
1.46
1.462
1.46
1.462
9,427,871
13,773,361
159845
SZ
2021-03-31T09:40:00
0.633
0.634
0.633
0.633
134,528
85,177.42
159915
SZ
2015-01-05T09:40:00
1.407
1.408
1.406
1.408
258,400
363,439.3
510050
SH
2015-01-05T09:41:00
2.585
2.586
2.583
2.584
10,039,900
25,951,240
510210
SH
2015-01-05T09:41:00
3.52
3.52
3.52
3.52
0
0
510300
SH
2015-01-05T09:41:00
3.614
3.614
3.612
3.613
8,664,800
31,313,570
510500
SH
2015-01-05T09:41:00
1.494
1.495
1.493
1.493
211,600
316,220.7
588000
SH
2020-11-16T09:41:00
1.462
1.468
1.462
1.468
9,280,443
13,590,016
159845
SZ
2021-03-31T09:41:00
0.634
0.634
0.632
0.634
101,217
64,077.145
159915
SZ
2015-01-05T09:41:00
1.407
1.409
1.407
1.409
276,600
389,562.9
510050
SH
2015-01-05T09:42:00
2.583
2.584
2.58
2.58
5,389,800
13,918,240
510210
SH
2015-01-05T09:42:00
3.511
3.511
3.511
3.511
4,300
15,097.3
510300
SH
2015-01-05T09:42:00
3.613
3.613
3.61
3.61
8,587,256
31,017,518
510500
SH
2015-01-05T09:42:00
1.491
1.494
1.491
1.491
174,300
259,908.7
588000
SH
2020-11-16T09:42:00
1.466
1.466
1.461
1.461
31,092,772
45,502,256
159845
SZ
2021-03-31T09:42:00
0.634
0.634
0.632
0.632
593,503
375,093.9
159915
SZ
2015-01-05T09:42:00
1.409
1.409
1.405
1.405
1,276,100
1,795,876.1
510050
SH
2015-01-05T09:43:00
2.581
2.581
2.575
2.576
5,779,100
14,904,432
510210
SH
2015-01-05T09:43:00
3.511
3.511
3.511
3.511
0
0
510300
SH
2015-01-05T09:43:00
3.609
3.611
3.605
3.605
12,146,052
43,825,484
510500
SH
2015-01-05T09:43:00
1.493
1.493
1.491
1.491
63,500
94,711.7
588000
SH
2020-11-16T09:43:00
1.461
1.462
1.459
1.462
15,812,942
23,086,982
159845
SZ
2021-03-31T09:43:00
0.632
0.632
0.632
0.632
5,070,336
3,204,452.2
159915
SZ
2015-01-05T09:43:00
1.407
1.407
1.402
1.405
890,600
1,251,062
510050
SH
2015-01-05T09:44:00
2.576
2.58
2.575
2.58
17,574,012
45,297,020
510210
SH
2015-01-05T09:44:00
3.511
3.511
3.511
3.511
0
0
End of preview. Expand in Data Studio

China Exchange-Traded Funds 1-Minute OHLCV

Minute-level OHLCV bars for selected exchange-listed Chinese ETFs. The release uses a stable Parquet schema, one canonical file per instrument, and machine-readable coverage reports.

Dataset summary

This snapshot contains 4,058,681 rows for 7 instruments across selected exchange-listed Chinese ETFs. It covers 2015-01-05 09:30:00 through 2026-08-20 15:00:00. Prices are unadjusted. Volume is stored in shares, turnover in CNY, and timezone-naive timestamps are interpreted as Asia/Singapore (UTC+8).

Item Value
Schema version 1
Instruments with bars 7
Minute-bar rows 4,058,681
Canonical Parquet files 7
Normalized data size 0.05 GB
First timestamp 2015-01-05 09:30:00
Last timestamp 2026-08-20 15:00:00
Snapshot build time 2026-08-21T16:41:46+08:00
Calendar/listing instrument-days before market-status audit 16,842
Observed instrument-trading days 16,841
Instrument-days without observed bars 1
Raw calendar/listing coverage before market-status audit 99.9941%
Instruments with no-bar days before market-status audit 1
Market-wide missing trading days inside the published span 0

Scope: this repository contains only the selected ETFs represented in the published inventory; it is not a complete universe of China-listed ETFs. A-share equities are excluded and published separately.

Dataset Viewer and subsets

The canonical data uses one Parquet file per instrument. Asking the Hub to inspect all 7 remote files as one Viewer split can time out. The explicit subsets below keep the Viewer usable without changing or duplicating the canonical dataset.

Subset Contents Rows
bars_sample (default) First up to 64 chronological bars from every published instrument; deterministic and not synthetic 448
instrument_coverage One row per published instrument with path, time range, record count, and trading-day coverage 7
missing_intervals Consecutive eligible trading-day ranges with no observed bars 1
market_calendar Every calendar date labeled as trading day, weekend, or exchange closure, with market-wide bar availability 4,250
absent_instruments Eligible universe members with no published canonical file 0

The Viewer sample spans 7 instruments and is 0.01 MB. It exists only for browser inspection. The complete 4,058,681-row dataset remains under data/etf_1m/.

load_dataset("neigezhu/china-etf-1min-ohlcv") loads the default bars_sample subset. Use the file-level or full-snapshot methods below for the canonical bars.

Load a Viewer subset

from datasets import load_dataset

sample = load_dataset("neigezhu/china-etf-1min-ohlcv", "bars_sample", split="train")
coverage = load_dataset("neigezhu/china-etf-1min-ohlcv", "instrument_coverage", split="train")

Load one canonical instrument

from huggingface_hub import hf_hub_download
import pyarrow.parquet as pq

path = hf_hub_download(
    repo_id="neigezhu/china-etf-1min-ohlcv",
    filename="data/etf_1m/SH/510300.parquet",
    repo_type="dataset",
)
bars = pq.read_table(path)

Download and scan the complete snapshot

from pathlib import Path
from huggingface_hub import snapshot_download
import pyarrow.dataset as ds

root = Path(snapshot_download(
    repo_id="neigezhu/china-etf-1min-ohlcv",
    repo_type="dataset",
    allow_patterns=["data/etf_1m/*/*.parquet", "metadata/*"],
))
bars = ds.dataset(root / "data" / "etf_1m", format="parquet")

For reproducible research, pass a Hub commit SHA as revision= to hf_hub_download or snapshot_download.

Repository layout

data/etf_1m/{exchange}/{symbol}.parquet
viewer/bars_sample.parquet
viewer/instrument_coverage.parquet
viewer/missing_intervals.parquet
viewer/market_calendar.parquet
viewer/absent_instruments.parquet
metadata/coverage_by_instrument.csv
metadata/missing_intervals.csv
metadata/market_calendar.csv
metadata/absent_instruments.csv
metadata/summary.json
LICENSE
README.md

Each canonical instrument file is sorted by timestamp. Its logical key is (exchange, symbol, timestamp). Symbols remain strings so leading zeroes are preserved.

Bar schema and semantics

Field Parquet type Unit / meaning
symbol string Security identifier without exchange suffix
exchange string SH, SZ, or BJ
timestamp timestamp[us] Timezone-naive minute label interpreted as Asia/Singapore (UTC+8)
open float64 Unadjusted opening price, CNY per share
high float64 Unadjusted high price, CNY per share
low float64 Unadjusted low price, CNY per share
close float64 Unadjusted closing price, CNY per share
volume int64 Traded shares during the minute
turnover float64 Traded value during the minute, CNY
  • Frequency: 1 minute.
  • Regular session labels: 09:30–11:30 and 13:00–15:00.
  • Price adjustment: none; corporate-action adjustment factors are not included.
  • Storage: Zstandard-compressed Parquet with statistics and bounded row groups.

Coverage and quality reports

metadata/coverage_by_instrument.csv is the canonical inventory. It records each file path, observed range, row count, expected and observed trading days, and coverage status. metadata/missing_intervals.csv groups eligible trading-day ranges with no observed bars. metadata/market_calendar.csv labels every date as trading_day, weekend, or exchange_closed, and records whether any published instrument has bars on that date. metadata/absent_instruments.csv lists eligible instruments without a published file. metadata/summary.json provides snapshot-level counts for automated checks.

Coverage is evaluated against an exchange trading calendar and each instrument's listing range. Weekends and exchange-declared closures, including statutory holiday closures, are excluded from expected trading days. Dates before listing and after known delisting are also excluded.

The value 1 instrument-day without observed bars is an aggregate over instruments, not a count of distinct calendar dates. If 100 instruments have no bars on one open day, that contributes 100 no-bar instrument-days. Within the published span, 0 exchange trading days have no bars for any instrument.

This snapshot does not publish an instrument-day suspension audit, so a no-bar day must not be interpreted as a verified collection gap from this repository alone.

Construction and validation

This snapshot is built by normalizing collected minute-bar files to the public schema, then sorting and deduplicating records by instrument and timestamp. Coverage reports are regenerated from the published Parquet files. This ETF release does not claim independent multi-source corroboration.

Limitations

  • This is a historical snapshot, not a real-time feed.
  • Coverage varies by instrument and is not gap-free; inspect instrument_coverage before research or backtesting.
  • Prices are unadjusted and the release does not include corporate actions or adjustment factors.
  • Minute OHLCV does not contain orders, individual trades, order-book state, participant identities, or latency information.
  • Provider-level provenance is intentionally not exposed, so it cannot be independently audited from the repository alone.
  • Floating-point prices and turnover should not be treated as exact decimal accounting values.

Related dataset

For A-share equities, use the separate China A-Share Equities 1-Minute OHLCV dataset. The schemas are compatible, but repository paths, universes, row counts, and coverage metrics are independent.

Versioning, license, and citation

  • Dataset schema version: 1.
  • License: Apache License 2.0.
  • Updates preserve the canonical path and field contract. Consumers that require an immutable snapshot should pin a Hub commit SHA.
@dataset{neigezhu_china_etf_1m_ohlcv,
  author    = {neigezhu},
  title     = {China Exchange-Traded Funds 1-Minute OHLCV},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/neigezhu/china-etf-1min-ohlcv}
}

中文说明

数据集概览

本快照包含选定的中国上市 ETF,共 7 个证券、4,058,681 条 1 分钟 OHLCV,时间范围为 2015-01-05 09:30:002026-08-20 15:00:00。价格不复权,成交量单位为股,成交额单位为人民币。Parquet 的 timestamp 不携带时区,统一按 Asia/Singapore(UTC+8)解释。

范围说明:本仓库只包含发布清单中的选定 ETF,并非中国上市 ETF 全量库;A 股股票不在本仓库内,另行发布。

Dataset Viewer

主数据保持“每个证券一个 Parquet 文件”,共有 7 个文件。Hugging Face 若把这些远程文件作为一个 Viewer split 逐个读取元数据会超时,因此仓库显式配置了五个可用子集:

  • bars_sample:默认子集;每个已发布证券取最早不超过 64 条记录,共 448 条。样本是确定性的真实记录,不是合成数据。
  • instrument_coverage:每个已发布证券一行,包含文件路径、记录数、起止时间和交易日覆盖。
  • missing_intervals:连续缺失交易日区间。
  • market_calendar:逐日标记交易日、周末或交易所休市日,并标记当天全市场是否至少有一条分钟数据。
  • absent_instruments:应在证券范围内但没有主数据文件的证券。

Viewer 只用于浏览。完整的 4,058,681 条记录仍位于 data/etf_1m/。直接调用 load_dataset("neigezhu/china-etf-1min-ohlcv") 会读取默认的 bars_sample,完整数据应使用上面的单证券下载或全快照下载方式。

数据约定

  • 逻辑主键:exchange + symbol + timestamp
  • 单个证券文件按 timestamp 升序排列。
  • 交易所代码:SHSZBJ
  • 常规交易时段:09:30–11:30、13:00–15:00。
  • 价格:人民币/股,不复权。
  • 成交量:股。
  • 成交额:人民币。
  • 时间:无时区 Parquet 时间戳,按 Asia/Singapore(UTC+8)解释。

构建与质量

本快照将已采集的分钟文件规范化到公开字段,并按证券和时间戳排序、去重;覆盖报告由最终发布的 Parquet 文件重新生成。本 ETF 版本不声明经过独立多源交叉核验。

覆盖率按交易所交易日历和证券上市区间计算。周末、法定节假日休市和交易所公告休市日不进入应有交易日;上市前和已知退市后的日期也不计入。

当前共有 16,842 个日历/上市区间内证券交易日16,841 个已观察证券交易日1 个无分钟记录证券日。这个无记录数是“证券 × 交易日”的合计,不是不同自然日数量:同一个交易日有 100 只证券无记录会计 100。发布区间内,全市场所有证券同时没有数据的交易日为 0 天

研究和回测前应同时检查 instrument_coveragemissing_intervalsmarket_calendar。本快照未发布逐证券日停牌核验表,因此不能仅凭无分钟记录判定为采集缺口。

局限

  • 这是历史快照,不是实时行情。
  • 不同证券的覆盖范围不同。
  • 数据不复权,不包含公司行动和复权因子。
  • 分钟 OHLCV 不包含逐笔成交、订单簿、参与者身份或延迟信息。
  • 仓库不披露数据提供方名称,因此不能仅从公开文件独立审计提供方级别的来源。

相关数据集

A 股股票数据见独立的 China A-Share Equities 1-Minute OHLCV。两套数据字段兼容,但仓库路径、证券范围、记录数和覆盖指标彼此独立。

版本与许可

  • schema 版本:1
  • 许可:Apache License 2.0
  • 需要严格复现时,请在下载接口中固定 Hugging Face commit SHA。
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