THULab/traqq_weekly_activity

Weekly Activity Data 24-28 June 2024 (TsFile)

This dataset is the Apache TsFile conversion of traqq/weekly_activity_data_jul24_jul28. The source CSV contains one daily activity aggregate for each anonymized employee.

Modalities: Time-series.

Overview

• Source revision: 0393412574b01590be365eaae427f02b1dee3012
• Source file: weekly_activity_data_24.06_28.06.csv
• Rows/employee-days: 328
• Distinct users: 67
• Dates: 2024-06-24 through 2024-06-28 (five daily dates)
• Converted file: traqq_weekly_activity.tsfile (76,966 bytes)
• Split: train

The repository identifier contains Jul24-Jul28, but the source filename and records cover June 24-28, 2024; the actual record dates are reported here.

TsFile schema

The table is traqq_weekly_activity. Each user_id is a TsFile device, with one observation per user and calendar date.

Column	Role	Type	Meaning
Time	TIME	INT64 (ms)	UTC-midnight epoch milliseconds from user_date
user_id	TAG	STRING	Source user_Id, normalized to lowercase spelling
start_time, end_time	FIELD	STRING	Source daily start/end clock strings
work_duration	FIELD	INT64	Source duration value, unchanged
activity_percentage	FIELD	DOUBLE	Source activity percentage, unchanged
duration_manual, duration_idle, duration_deleted	FIELD	INT64	Source duration aggregates, unchanged

Conversion notes

• user_date is parsed as a calendar date and encoded as Time at UTC midnight. The redundant source date string is not duplicated as a FIELD.
• The source spelling user_Id is renamed to the user_id TAG; its values are not recoded.
• Start/end times remain strings. They describe the workday interval and are not combined into a false instantaneous timestamp.
• All 328 rows and all source activity fields are retained. Duplicate (user_id, Time) keys are rejected rather than silently overwritten.

Read example

from tsfile import TsFileReader

path = "traqq_weekly_activity.tsfile"
with TsFileReader(path) as reader:
    with reader.query_table(
        "traqq_weekly_activity",
        ["work_duration", "activity_percentage"],
        batch_size=1024,
    ) as result:
        batch = result.read_arrow_batch()
        if batch is not None:
            print(batch.to_pandas().head())

Source & license

• Original dataset: https://huggingface.co/datasets/traqq/weekly_activity_data_jul24_jul28
• Author / publisher: Traqq
• License: not declared by the original dataset; please defer to the original.

Usage

Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:

from pathlib import Path
from tsfile import TsFileReader

path = Path("traqq_weekly_activity.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())