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Dataset research report

Fish research report

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

storageHf descriptionscikit-learn--fish.parquet view_list159 rows

Executive Summary

Dataset Summary Dataset recording various measurements of 7 different species of fish at a fish market. Predictive models can be used to predict weight, species, etc. Feature Descriptions Species - Species name of fish Weight - Weight of fish in grams Length1 - Vertical length in cm Length2 - Diagonal length in cm Length3 - Cross length in cm Height - Height in cm Width - Width in cm Acknowledgments Dataset created by Aung Pyae, and found on… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/Fish.

Finding 1The dataset has 159 rows available in the catalog.
Finding 2The catalog exposes 7 documented or inferred columns.
Finding 3Helix has 6 ready query prompts for this dataset.
Finding 4This report includes 5 generated chart views.

Research Context

Fish: 159 rows by 7 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows159
Columns7
Numeric cols6
Categorical cols1

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

# Speciestext Weightfloat Length1float Length2float Length3float Heightfloat Widthfloat
1 Bream24223.225.43011.524.02
2 Bream2902426.331.212.484.306
3 Bream34023.926.531.112.384.696
4 Bream36326.32933.512.734.455
5 Bream43026.5293412.445.134
6 Bream45026.829.734.713.64.927

Data Dictionary

  • Species categorical
  • Weight numeric
  • Length1 numeric
  • Length2 numeric
  • Length3 numeric
  • Height numeric
  • Width 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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