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Dataset research report

Mnist research report

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

storageHf descriptionmnist.parquet view_list500 rows

Executive Summary

Dataset Card for MNIST Dataset Summary The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class. Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/ylecun/mnist.

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

Research Context

Mnist: 500 rows by 2 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows500
Columns2
Numeric cols1
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

# imagetext labelinteger
1 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75518CF29550>5
2 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75513FF95E50>0
3 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75513FF95090>4
4 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75513FF15810>1
5 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75513FF15A70>9
6 <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28 at 0x75513FF15810>2

Data Dictionary

  • image categorical
  • label 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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