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CulmenLength float64 33.5 55.9 ⌀ | CulmenDepth float64 13.1 21.5 ⌀ | FlipperLength float64 172 230 ⌀ | BodyMass float64 2.85k 6k ⌀ | Species int64 0 2 |
|---|---|---|---|---|
40.9 | 16.8 | 191 | 3,700 | 0 |
42.2 | 18.5 | 180 | 3,550 | 0 |
45.8 | 18.9 | 197 | 4,150 | 0 |
40.2 | 20.1 | 200 | 3,975 | 0 |
35.9 | 16.6 | 190 | 3,050 | 0 |
42.8 | 18.5 | 195 | 4,250 | 0 |
41.3 | 21.1 | 195 | 4,400 | 0 |
38.1 | 18.6 | 190 | 3,700 | 0 |
41.1 | 18.6 | 189 | 3,325 | 0 |
44.1 | 19.7 | 196 | 4,400 | 0 |
40.2 | 17 | 176 | 3,450 | 0 |
41.5 | 18.5 | 201 | 4,000 | 0 |
42.1 | 19.1 | 195 | 4,000 | 0 |
42.5 | 20.7 | 197 | 4,500 | 0 |
40.6 | 19 | 199 | 4,000 | 0 |
40.9 | 18.9 | 184 | 3,900 | 0 |
37 | 16.5 | 185 | 3,400 | 0 |
40.6 | 18.6 | 183 | 3,550 | 0 |
41.3 | 20.3 | 194 | 3,550 | 0 |
42 | 19.5 | 200 | 4,050 | 0 |
39 | 17.5 | 186 | 3,550 | 0 |
37 | 16.9 | 185 | 3,000 | 0 |
37.2 | 19.4 | 184 | 3,900 | 0 |
36.4 | 17.1 | 184 | 2,850 | 0 |
35.5 | 16.2 | 195 | 3,350 | 0 |
35.9 | 19.2 | 189 | 3,800 | 0 |
44.1 | 18 | 210 | 4,000 | 0 |
37.7 | 16 | 183 | 3,075 | 0 |
36.8 | 18.5 | 193 | 3,500 | 0 |
37.5 | 18.9 | 179 | 2,975 | 0 |
43.1 | 19.2 | 197 | 3,500 | 0 |
40.3 | 18 | 195 | 3,250 | 0 |
38.2 | 20 | 190 | 3,900 | 0 |
39.5 | 17.4 | 186 | 3,800 | 0 |
36.9 | 18.6 | 189 | 3,500 | 0 |
35 | 17.9 | 190 | 3,450 | 0 |
37.9 | 18.6 | 172 | 3,150 | 0 |
38.6 | 17.2 | 199 | 3,750 | 0 |
36 | 18.5 | 186 | 3,100 | 0 |
37.7 | 18.7 | 180 | 3,600 | 0 |
41 | 20 | 203 | 4,725 | 0 |
36.7 | 19.3 | 193 | 3,450 | 0 |
34.1 | 18.1 | 193 | 3,475 | 0 |
36 | 17.1 | 187 | 3,700 | 0 |
39.5 | 17.8 | 188 | 3,300 | 0 |
36 | 17.8 | 195 | 3,450 | 0 |
38.1 | 17 | 181 | 3,175 | 0 |
38.8 | 17.6 | 191 | 3,275 | 0 |
35.7 | 16.9 | 185 | 3,150 | 0 |
41.4 | 18.5 | 202 | 3,875 | 0 |
37.8 | 17.1 | 186 | 3,300 | 0 |
40.6 | 17.2 | 187 | 3,475 | 0 |
36 | 17.9 | 190 | 3,450 | 0 |
37.8 | 17.3 | 180 | 3,700 | 0 |
36.6 | 17.8 | 185 | 3,700 | 0 |
39.3 | 20.6 | 190 | 3,650 | 0 |
35.2 | 15.9 | 186 | 3,050 | 0 |
41.1 | 18.2 | 192 | 4,050 | 0 |
37.3 | 16.8 | 192 | 3,000 | 0 |
42.7 | 18.3 | 196 | 4,075 | 0 |
39.6 | 17.7 | 186 | 3,500 | 0 |
37.8 | 18.1 | 193 | 3,750 | 0 |
34 | 17.1 | 185 | 3,400 | 0 |
36.4 | 17 | 195 | 3,325 | 0 |
38.6 | 21.2 | 191 | 3,800 | 0 |
37.5 | 18.5 | 199 | 4,475 | 0 |
38.1 | 17.6 | 187 | 3,425 | 0 |
43.2 | 18.5 | 192 | 4,100 | 0 |
37.9 | 18.6 | 193 | 2,925 | 0 |
36.2 | 17.2 | 187 | 3,150 | 0 |
37.6 | 17 | 185 | 3,600 | 0 |
36.3 | 19.5 | 190 | 3,800 | 0 |
35.1 | 19.4 | 193 | 4,200 | 0 |
34.6 | 21.1 | 198 | 4,400 | 0 |
40.8 | 18.4 | 195 | 3,900 | 0 |
37.8 | 18.3 | 174 | 3,400 | 0 |
41.1 | 18.1 | 205 | 4,300 | 0 |
40.6 | 18.8 | 193 | 3,800 | 0 |
39 | 17.1 | 191 | 3,050 | 0 |
38.3 | 19.2 | 189 | 3,950 | 0 |
33.5 | 19 | 190 | 3,600 | 0 |
37.8 | 20 | 190 | 4,250 | 0 |
36.7 | 18.8 | 187 | 3,800 | 0 |
41.1 | 19.1 | 188 | 4,100 | 0 |
39.6 | 17.2 | 196 | 3,550 | 0 |
41.1 | 17.6 | 182 | 3,200 | 0 |
38.1 | 16.5 | 198 | 3,825 | 0 |
39.2 | 19.6 | 195 | 4,675 | 0 |
39.7 | 18.4 | 190 | 3,900 | 0 |
41.4 | 18.6 | 191 | 3,700 | 0 |
37.2 | 18.1 | 178 | 3,900 | 0 |
38.7 | 19 | 195 | 3,450 | 0 |
null | null | null | null | 0 |
35.7 | 18 | 202 | 3,550 | 0 |
37.6 | 19.3 | 181 | 3,300 | 0 |
35.3 | 18.9 | 187 | 3,800 | 0 |
39 | 18.7 | 185 | 3,650 | 0 |
38.6 | 17 | 188 | 2,900 | 0 |
46 | 21.5 | 194 | 4,200 | 0 |
39.2 | 21.1 | 196 | 4,150 | 0 |
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Penguin Species Classification
Dataset Summary
Penguin Species Classification is a small tabular dataset for predicting which of three penguin species an observation belongs to based on physical measurements. The target label is encoded as Species, where 0 = Adelie, 1 = Gentoo, and 2 = Chinstrap.
This uploaded version preserves the original rows, including missing feature values, so users can decide how they want to clean and prepare the data for their own modeling workflows.
Dataset Structure
train: 274 rowstest: 70 rows- 2 rows contain missing measurement values and were intentionally retained
Label Mapping
| Label | Species |
|---|---|
0 |
Adelie |
1 |
Gentoo |
2 |
Chinstrap |
Features
| Column | Type | Description |
|---|---|---|
CulmenLength |
float | Culmen length measurement. |
CulmenDepth |
float | Culmen depth measurement. |
FlipperLength |
integer | Flipper length measurement. |
BodyMass |
integer | Body mass measurement. |
Species |
integer label | Target class for penguin species. |
Dataset Dictionary
| Field | Role | Notes |
|---|---|---|
CulmenLength |
feature | Numeric morphological feature used for classification. |
CulmenDepth |
feature | Numeric morphological feature used for classification. |
FlipperLength |
feature | Numeric morphological feature used for classification. |
BodyMass |
feature | Numeric morphological feature used for classification. |
Species |
target | Encoded multiclass target with three species labels. |
Split Details
The train/test split was created using a reproducible stratified random split with a fixed seed so class balance is preserved across both splits.
| Split | Label 0 | Label 1 | Label 2 | Total |
|---|---|---|---|---|
train |
120 | 98 | 54 | 274 |
test |
31 | 25 | 14 | 70 |
First 5 Rows
| CulmenLength | CulmenDepth | FlipperLength | BodyMass | Species |
|---|---|---|---|---|
| 39.1 | 18.7 | 181 | 3750 | 0 |
| 39.5 | 17.4 | 186 | 3800 | 0 |
| 40.3 | 18.0 | 195 | 3250 | 0 |
| 0 | ||||
| 36.7 | 19.3 | 193 | 3450 | 0 |
Intended Use
This dataset is suitable for:
- multiclass classification practice
- introductory tabular machine learning workflows
- feature scaling and model comparison exercises
- teaching supervised learning concepts
Limitations
- This is a small dataset intended for experimentation and learning.
- The source file provided did not include provenance or license metadata, so those should be added if you want a more complete Hub listing.
- Users need to handle missing values themselves before training models that require complete inputs.
- Performance estimates can vary because the classes are not perfectly balanced.
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