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Dataset research report

Adult Census Income research report

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

storageHf descriptionscikit-learn--adult-census-income.parquet view_list500 rows

Executive Summary

Adult Census Income Dataset The following was retrieved from UCI machine learning repository. This data was extracted from the 1994 Census bureau database by Ronny Kohavi and Barry Becker (Data Mining and Visualization, Silicon Graphics). A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1) && (HRSWK>0)). The prediction task is to determine whether a person makes over $50K a year. Description of fnlwgt (final weight)… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/adult-census-income.

Finding 1The dataset has 500 rows available in the catalog.
Finding 2The catalog exposes 15 documented or inferred columns.
Finding 3Helix has 5 ready query prompts for this dataset.
Finding 4This report includes 5 generated chart views.

Research Context

Adult Census Income: 500 rows by 15 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows500
Columns15
Numeric cols6
Categorical cols9

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

# ageinteger workclasstext fnlwgtinteger educationtext education.numinteger marital.statustext occupationtext relationshiptext
1 90?77053HS-grad9Widowed?Not-in-family
2 82Private132870HS-grad9WidowedExec-managerialNot-in-family
3 66?186061Some-college10Widowed?Unmarried
4 54Private1403597th-8th4DivorcedMachine-op-inspctUnmarried
5 41Private264663Some-college10SeparatedProf-specialtyOwn-child
6 34Private216864HS-grad9DivorcedOther-serviceUnmarried

Data Dictionary

  • age numeric
  • workclass categorical
  • fnlwgt numeric
  • education text
  • education.num numeric
  • marital.status categorical
  • occupation text
  • relationship categorical
  • race categorical
  • sex categorical
  • capital.gain numeric
  • capital.loss numeric
  • hours.per.week numeric
  • native.country categorical
  • income categorical

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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