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Dataset research report

Youtube Transcriptions research report

A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.

storageHf descriptionjamescalam--youtube-transcriptions.parquet view_list500 rows

Executive Summary

The YouTube transcriptions dataset contains technical tutorials (currently from James Briggs, Daniel Bourke, and AI Coffee Break) transcribed using OpenAI's Whisper (large). Each row represents roughly a sentence-length chunk of text alongside the video URL and timestamp. Note that each item in the dataset contains just a short chunk of text. For most use cases you will likely need to merge multiple rows to create more substantial chunks of text, if you need to do that, this code snippet will… See the full description on the dataset page: https://huggingface.co/datasets/jamescalam/youtube-transcriptions.

Finding 1The dataset has 500 rows available in the catalog.
Finding 2The catalog exposes 9 documented or inferred columns.
Finding 3Helix has 5 ready query prompts for this dataset.
Finding 4This report includes 2 generated chart views.

Research Context

Youtube Transcriptions: 500 rows by 9 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows500
Columns9
Numeric cols2
Categorical cols5

Chart Evidence

These views are generated from the dataset profile. Each chart is paired with a Helix query so it can be opened, adjusted, and exported.

Follow-Up Queries

Preview Rows

# titletext publishedtext urltext video_idtext channel_idtext idtext texttext startfloat
1 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t0.0Hi, welcome to the video.0
2 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t3.0So this is the fourth video in a Transformers3
3 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t9.36from Scratch mini series.9.36
4 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t11.56So if you haven't been following along,11.56
5 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t15.84we've essentially covered what you can see on the screen.15.84
6 Training and Testing an Italian BERT - Transformers From Scratch #42021-07-06 13:00:03 UTChttps://youtu.be/35Pdoyi6ZoQ35Pdoyi6ZoQUCv83tO5cePwHMt1952IVVHw35Pdoyi6ZoQ-t18.48So we got some data.18.48

Data Dictionary

  • title categorical
  • published categorical
  • url categorical
  • video_id categorical
  • channel_id categorical
  • id text
  • text text
  • start numeric
  • end numeric

Method And Limits

  • Load the catalog entry and preview rows from the processed dataset file.
  • Infer numeric, categorical, time, and location fields from real columns.
  • Generate a small set of defensive Plotly chart specifications from that profile.
  • Expose each chart idea as a query link so the report can be rerun or exported in Helix.

This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.

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