Dataset research report
Iris research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Iris Species Dataset The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository. It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other. The dataset is taken from UCI Machine Learning Repository's… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/iris.
Research Context
Iris: 150 rows by 6 columns. These exploratory charts are generated automatically from the data - open the dataset in Helix to ask your own questions.
Data Profile
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.
Total SepalLengthCm by Species
Top Species values ranked by summed SepalLengthCm.
Open and export this chartSepalLengthCm vs SepalWidthCm
SepalLengthCm vs SepalWidthCm, coloured by Species.
Open and export this chartCorrelation of numeric columns
Pearson correlation between numeric columns.
Open and export this chartSepalLengthCm by Species
Spread of SepalLengthCm across Species groups.
Open and export this chartFollow-Up Queries
Preview Rows
| # | Idinteger | SepalLengthCmfloat | SepalWidthCmfloat | PetalLengthCmfloat | PetalWidthCmfloat | Speciestext |
|---|---|---|---|---|---|---|
| 1 | 1 | 5.1 | 3.5 | 1.4 | 0.2 | Iris-setosa |
| 2 | 2 | 4.9 | 3 | 1.4 | 0.2 | Iris-setosa |
| 3 | 3 | 4.7 | 3.2 | 1.3 | 0.2 | Iris-setosa |
| 4 | 4 | 4.6 | 3.1 | 1.5 | 0.2 | Iris-setosa |
| 5 | 5 | 5 | 3.6 | 1.4 | 0.2 | Iris-setosa |
| 6 | 6 | 5.4 | 3.9 | 1.7 | 0.4 | Iris-setosa |
Data Dictionary
- Id numeric
- SepalLengthCm numeric
- SepalWidthCm numeric
- PetalLengthCm numeric
- PetalWidthCm numeric
- Species 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.