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 # Video files - compressed
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diff --git a/README.md b/README.md
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+---
+license: other
+task_categories:
+- time-series-forecasting
+tags:
+- time-series
+- tsfile
+pretty_name: m5 (TsFile format)
+---
+
+# m5 — TsFile 格式
+
+本目录是 [`autogluon/fev_datasets`](https://huggingface.co/datasets/autogluon/fev_datasets) 中 **m5** 子集转换为 [Apache TsFile](https://tsfile.apache.org/) 格式的版本。
+
+## 来源与引用
+
+- **原始来源**：https://www.kaggle.com/competitions/m5-forecasting-accuracy
+- **论文/引用**：[[15]](https://doi.org/10.1016/j.ijforecast.2021.11.013)
+- **统一格式合集**：[autogluon/fev_datasets](https://huggingface.co/datasets/autogluon/fev_datasets)
+
+> 本数据由外部来源转换为统一格式后再转为 TsFile。许可与引用以**原始来源**为准，我们不对原始数据主张任何权利。除非另有说明，数据仅供研究用途。
+
+## 数据统计
+
+| 频率 | 序列数 | 中位长度 | 观测点数 | 动态列 | 静态列 | 文件 |
+|---|---|---|---|---|---|---|
+| 1D | 30,490 | 1,810 | 428,849,460 | 9 | 5 | `1D/1D_1..1D_46.tsfile`（46 片） |
+| 1M | 30,490 | 58 | 13,805,685 | 9 | 5 | `1M/1M_1..1M_2.tsfile`（2 片） |
+| 1W | 30,490 | 257 | 60,857,703 | 9 | 5 | `1W/1W_1..1W_7.tsfile`（7 片） |
+
+## TsFile 存储模型
+
+- 每条原始序列（`id`）→ 一个 **device**（TAG 维度）。
+- 静态协变量列 → 也作 **TAG**（device 元数据）：`item_id, dept_id, cat_id, store_id, state_id`。
+- 随时间变化的 target / 动态协变量 → **measurement**（FIELD）。
+- `timestamp` → `Time`（INT64 毫秒）。
+- 表名：m5_1D, m5_1M, m5_1W。
+
+### 列含义
+
+| 列 | 角色 | TsFile 类型 |
+|---|---|---|
+| `Time` | Time（时间列） | INT64 |
+| `id` | TAG（device 维度） | STRING |
+| `item_id` | TAG（device 维度） | STRING |
+| `dept_id` | TAG（device 维度） | STRING |
+| `cat_id` | TAG（device 维度） | STRING |
+| `store_id` | TAG（device 维度） | STRING |
+| `state_id` | TAG（device 维度） | STRING |
+| `target` | FIELD（measurement） | FLOAT |
+| `snap_CA` | FIELD（measurement） | BOOLEAN |
+| `snap_TX` | FIELD（measurement） | BOOLEAN |
+| `snap_WI` | FIELD（measurement） | BOOLEAN |
+| `sell_price` | FIELD（measurement） | FLOAT |
+| `event_Cultural` | FIELD（measurement） | BOOLEAN |
+| `event_National` | FIELD（measurement） | BOOLEAN |
+| `event_Religious` | FIELD（measurement） | BOOLEAN |
+| `event_Sporting` | FIELD（measurement） | BOOLEAN |
+
+## 转换说明
+
+- 每行原始数据是一整条序列 `(id, timestamp[], 各 target[])`，纵向打平为长表后写入 TsFile。
+- 数值类型按源列自适应：float32→FLOAT、float64→DOUBLE、整数→INT64、bool→BOOLEAN。
+- 时间精度：毫秒（INT64）。
+- 大表会被工具自动分片为 `<名>_1.tsfile`、`<名>_2.tsfile` …，同属一个逻辑表。
+
+## 读取示例
+
+```python
+from tsfile import TsFileReader
+
+reader = TsFileReader("1D/1D.tsfile")
+schemas = reader.get_all_table_schemas()
+# 表名：m5_1D；列见下方"列含义"。
+```