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Dataset research report

Heart Failure research report

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

storageHf descriptionmstz--heart-failure.parquet view_list299 rows

Executive Summary

Heart failure The Heart failure dataset from Kaggle. Predict patient death from earth failure given some personal medical data . Configurations and tasks Configuration Task Description death Binary classification Did the patient die? Usage from datasets import load_dataset dataset = load_dataset("mstz/heart_failure", "death")["train"] Features Feature Type age int8 has_anaemia int8… See the full description on the dataset page: https://huggingface.co/datasets/mstz/heart_failure.

Finding 1The dataset has 299 rows available in the catalog.
Finding 2The catalog exposes 13 documented or inferred columns.
Finding 3Helix has 6 ready query prompts for this dataset.
Finding 4This report includes 5 generated chart views.

Research Context

Heart Failure: 299 rows by 13 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.

Data Profile

Rows299
Columns13
Numeric cols8
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

# ageinteger has_anaemiaboolean creatinine_phosphokinase_concentration_in_bloodfloat has_diabetesboolean heart_ejection_fractionfloat has_high_blood_pressureboolean platelets_concentration_in_bloodfloat serum_creatinine_concentration_in_bloodfloat
1 75False582False20True2650001.9
2 55False7861False38False2.634e+051.1
3 65False146False20False1620001.3
4 50True111False20False2100001.9
5 65True160True20False3270002.7
6 90True47False40True2040002.1

Data Dictionary

  • age numeric
  • has_anaemia bool
  • creatinine_phosphokinase_concentration_in_blood numeric
  • has_diabetes bool
  • heart_ejection_fraction numeric
  • has_high_blood_pressure bool
  • platelets_concentration_in_blood numeric
  • serum_creatinine_concentration_in_blood numeric
  • serum_sodium_concentration_in_blood numeric
  • is_male bool
  • is_smoker bool
  • days_in_study datetime
  • is_dead 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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