Datasets:

smilegeng
/

youtube_trending_2019_2020

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 304, in _scan_metadata
                  from tsfile.constants import TIME_COLUMN, ColumnCategory
              ModuleNotFoundError: No module named 'tsfile'
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 66, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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youtube_trending_2019_2020

This repository contains a TsFile conversion of the Hugging Face dataset jettisonthenet/timeseries_trending_youtube_videos_2019-04-15_to_2020-04-15.

The source dataset card / Viewer identifies the dataset as a YouTube trending video time-series dataset. The source repository contains videostats.csv and the Hugging Face Viewer exposes the default/train split with about 1.54M rows. The locally downloaded source file used for this conversion contains 1,541,128 rows.

Original Dataset

Original dataset: https://huggingface.co/datasets/jettisonthenet/timeseries_trending_youtube_videos_2019-04-15_to_2020-04-15
Source file used for conversion: videostats.csv
Split used: train
Local downloaded rows: 1,541,128
Distinct ytvideoid values in the downloaded file: 11,369
Time range in the downloaded file: 2019-04-15 04:42:49 to 2020-04-14 23:31:06

The original columns are:

Column	Description used in this conversion
`videostatsid`	Source row/statistics identifier
`ytvideoid`	YouTube video identifier
`views`	View count
`comments`	Comment count
`likes`	Like count
`dislikes`	Dislike count
`timestamp`	Source timestamp

The source dataset does not contain video files, frames, audio, thumbnails, or other media binaries. ytvideoid is an identifier only.

TsFile Conversion

The conversion was performed from the source CSV into staged Parquet and then into TsFile using the repository workflow.

Generated files:

youtube_trending_2019_2020_1.tsfile
youtube_trending_2019_2020_2.tsfile

Schema-level conversion choices:

timestamp was parsed into the TsFile Time column at millisecond precision.
The original timestamp value was preserved as source_timestamp_ms.
ytvideoid was declared as a TAG, so each YouTube video ID is represented as a separate device series.
views, comments, likes, and dislikes were retained as INT64 fields.
videostatsid was retained as an INT64 field for traceability.
No original source columns were dropped.

Duplicate timestamp handling:

The source CSV contains 89 duplicate (ytvideoid, timestamp) pairs. TsFile requires timestamps within one device series to be unique/ordered for reliable import. For those duplicate pairs only, the converted Time value was disambiguated by adding a zero-based millisecond offset ordered by videostatsid. The unadjusted source timestamp remains available in source_timestamp_ms.

Validation

The staged Parquet file contains:

1,541,128 rows
11,369 distinct ytvideoid tag values
0 duplicate (ytvideoid, Time) pairs after conversion

Both generated .tsfile files were validated locally as present and non-empty.

Downloads last month: 67

Total file size:

25.1 MB