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Datasets:
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Tasks:
Time Series Forecasting
Modalities:
Time-series
Sub-tasks:
univariate-time-series-forecasting
multivariate-time-series-forecasting
Size:
100K<n<1M
ArXiv:
Tags:
forecasting
tsfile
format:tsfile
timeseries
License:
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metadata 
license: other
task_categories:
  - time-series-forecasting
tags:
  - time-series
  - tsfile
  - format:tsfile
pretty_name: bizitobs_l2c (TsFile format)

bizitobs_l2c (TsFile format)

Source and Citation

This dataset was converted from external source data into a unified forecasting format and then into TsFile. Licensing and citation requirements follow the original source. We do not claim ownership of the original data. Unless otherwise stated, the data is intended for research use.

Dataset Statistics

Frequency Number of series Median length Observations Dynamic columns Static columns Files
1H 1 2,664 18,648 7 0 1H/1H.tsfile
5T 1 31,968 223,776 7 0 5T/5T.tsfile

TsFile Storage Model

  • Each original series (id) is stored as one TsFile device (TAG dimension).
  • Time-varying targets and dynamic covariates are stored as measurements (FIELDs).
  • timestamp is mapped to Time as INT64 milliseconds.
  • Table names: bizitobs_l2c_1H, bizitobs_l2c_5T.

Column Schema

Column Role TsFile type
Time Time column INT64
id TAG (device dimension) STRING
target_0 FIELD (measurement) FLOAT
target_1 FIELD (measurement) FLOAT
target_2 FIELD (measurement) FLOAT
target_3 FIELD (measurement) FLOAT
target_4 FIELD (measurement) FLOAT
target_5 FIELD (measurement) FLOAT
target_6 FIELD (measurement) FLOAT

Conversion Notes

  • Each original row stores one complete series (id, timestamp[], target and dynamic arrays). The converter flattens these nested rows into a long table before writing TsFile.
  • Numeric types are inferred from the source columns, for example float32 to FLOAT, float64 to DOUBLE, integers to INT64, and bool to BOOLEAN.
  • Time precision: milliseconds (INT64).
  • Large tables may be automatically sharded as <name>_1.tsfile, <name>_2.tsfile, and so on. These shards belong to the same logical table.

Reading Example 

from tsfile import TsFileReader

reader = TsFileReader("1H/1H.tsfile")
schemas = reader.get_all_table_schemas()
# Table name: bizitobs_l2c_1H; see \"Column Schema\" below.