Datasets / scikit-learn

Diabetes progression

Ten baseline variables against disease progression after a year.

442 rows11 columns scikit-learn

Worked examples

Each of these is a real run: the pipeline picked the columns, shaped the rows and chose the form. Open the trace to see what it decided and why.

Absolute correlation, so a strong negative relationship is not sorted to the bottom as though it were weak.

which variable correlates most with progression? — 10 rows charted from 442, drawn as a hbar

How it decided

Finding the data139 ms

Diabetes progression: 442 rows, 11 columns. all ten baseline variables against progression.

Shaping the data14 ms

442 rows in, 10 out across 2 columns. Absolute correlation, so a strong negative relationship is not sorted to the bottom as though it were weak.

Choosing the chart9 ms

hbar. A ranking across ten items: horizontal bars, strongest first.

Applying defaults1 ms

Palette, spacing, axis titles and legend placement applied. 0 issues found.

One point per patient, no aggregation: the spread around the trend is as much of the answer as the trend.

show BMI against progression — 442 rows charted from 442, drawn as a scatter

How it decided

Finding the data139 ms

Diabetes progression: 442 rows, 11 columns. bmi and progression.

Shaping the data7 ms

442 rows in, 442 out across 2 columns. One point per patient, no aggregation: the spread around the trend is as much of the answer as the trend.

Choosing the chart2 ms

scatter. Two measures, no category and no time: a scatter of the raw rows.

Applying defaults1 ms

Palette, spacing, axis titles and legend placement applied. 0 issues found.

11 columns, typed as the pipeline sees them — which is how it knows what can go on a time axis and what can be summed.

age	sex	bmi	bp	s1	s2	s3	s4	s5	s6	progression
0.0381	0.0507	0.0617	0.0219	-0.0442	-0.0348	-0.0434	-0.0026	0.0199	-0.0176	151.0
-0.0019	-0.0446	-0.0515	-0.0263	-0.0084	-0.0192	0.0744	-0.0395	-0.0683	-0.0922	75.0
0.0853	0.0507	0.0445	-0.0057	-0.0456	-0.0342	-0.0324	-0.0026	0.0029	-0.0259	141.0
-0.0891	-0.0446	-0.0116	-0.0367	0.0122	0.025	-0.036	0.0343	0.0227	-0.0094	206.0
0.0054	-0.0446	-0.0364	0.0219	0.0039	0.0156	0.0081	-0.0026	-0.032	-0.0466	135.0
-0.0927	-0.0446	-0.0407	-0.0194	-0.069	-0.0793	0.0413	-0.0764	-0.0412	-0.0963	97.0
-0.0455	0.0507	-0.0472	-0.016	-0.0401	-0.0248	0.0008	-0.0395	-0.0629	-0.0384	138.0
0.0635	0.0507	-0.0019	0.0666	0.0906	0.1089	0.0229	0.0177	-0.0358	0.0031	63.0