--- tags: - tsfile - timeseries - time-series - format:tsfile pretty_name: us_streamflow (TsFile) configs: - config_name: default data_files: - split: train path: us_streamflow.tsfile --- # us_streamflow (TsFile) Apache TsFile version of [`2imi9/us-power-climate-data-streamflow`](https://huggingface.co/datasets/2imi9/us-power-climate-data-streamflow). ## Overview This dataset provides daily streamflow observations from the U.S. Geological Survey (USGS) National Water Information System (NWIS) for rivers and streams located near a sampled subset of U.S. electric power plants. It is intended for studies of hydrologic constraints on power generation, climate vulnerability analysis, and machine-learning applications requiring hydrology–infrastructure relationships. - **Tables:** 1 TsFile table(s), 13,140 rows in total. - `us_streamflow`: 13,140 rows, 2022-01-01 00:00:00 鈫?2023-12-31 00:00:00.017000 (UTC) ## Schema (TsFile structure) ### `us_streamflow.tsfile` - **Time** (INT64, milliseconds) 鈥?the source `date` column. - **TAG**: none 鈥?the table is stored as a single device. - **FIELD** (5): `plant_code` (int64), `gauge_id` (string), `discharge_cfs` (double), `gauge_lat` (double), `gauge_lon` (double) ## Conversion notes - One TsFile per source table (1 tables). Tables whose source carries several entities per file are stored as one device per entity. - Time = the table's own clock column as INT64 milliseconds. The clock columns used here are `date`. - No column is dropped. Rows that share a timestamp inside one device are ordered by a 1 ms step in stable source order, so calendar columns keep their exact day. ## Usage > **Read this dataset with the Java SDK.** It is written with the `zstd` compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (`pip install tsfile`) implements only `UNCOMPRESSED`, `SNAPPY`, `GZIP` and `LZ4`; opening this file with it yields no rows. Read a converted file with the Apache TsFile Java SDK (`org.apache.tsfile:tsfile`): ```java import org.apache.tsfile.file.metadata.IDeviceID; import org.apache.tsfile.read.TsFileReader; import org.apache.tsfile.read.TsFileSequenceReader; import org.apache.tsfile.read.common.Path; import org.apache.tsfile.read.expression.QueryExpression; import org.apache.tsfile.read.query.dataset.QueryDataSet; import org.apache.tsfile.write.schema.MeasurementSchema; import java.util.ArrayList; import java.util.List; String path = "us_streamflow.tsfile"; try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path); TsFileReader reader = new TsFileReader(sequenceReader)) { // Devices are enumerated as IDeviceID objects. Tables with TAG columns // have multi-segment device ids that cannot be rebuilt from their string // form, so always use getAllDevices() rather than getAllDeviceIds(). for (IDeviceID device : sequenceReader.getAllDevices()) { List paths = new ArrayList<>(); for (MeasurementSchema schema : reader.getMeasurement(device)) { String name = schema.getMeasurementName(); if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) { paths.add(new Path(device, name, true)); } } QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null)); while (dataSet.hasNext()) { System.out.println(dataSet.next()); } } } ``` ## Source & license - Original dataset: [`2imi9/us-power-climate-data-streamflow`](https://huggingface.co/datasets/2imi9/us-power-climate-data-streamflow) - License: not declared (as declared by the original dataset).