palmerpenguins

The Palmer penguins dataset by Allison Horst, Alison Hill, and Kristen Gorman was first made publicly available as an R package. The goal of the Palmer Penguins dataset is to replace the highly overused Iris dataset for data exploration & visualization. Using this python package you can easily load the Palmer penguins into your python environment.

Artwork by @allison_horst

Installation

pip install palmerpenguins

Overview

Size measurements, clutch observations, and blood isotope ratios for 344 adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station, Antarctica Long Term Ecological Research (LTER) Program.

Examples

import pandas as pd
import seaborn as sns 
from palmerpenguins import load_penguins
sns.set_style('whitegrid')

penguins = load_penguins()
penguins.head()

  species     island  bill_length_mm  ...  body_mass_g     sex  year
0  Adelie  Torgersen            39.1  ...       3750.0    male  2007
1  Adelie  Torgersen            39.5  ...       3800.0  female  2007
2  Adelie  Torgersen            40.3  ...       3250.0  female  2007
3  Adelie  Torgersen             NaN  ...          NaN     NaN  2007
4  Adelie  Torgersen            36.7  ...       3450.0  female  2007
[5 rows x 8 columns]

g = sns.boxplot(x = 'island',
            y ='body_mass_g',
            hue = 'species',
            data = penguins,
            palette=['#FF8C00','#159090','#A034F0'],
            linewidth=0.3)
g.set_xlabel('Island')
g.set_ylabel('Body Mass')

g = sns.lmplot(x="flipper_length_mm",
               y="body_mass_g",
               hue="species",
               height=7,
               data=penguins,
               palette=['#FF8C00','#159090','#A034F0'])
g.set_xlabels('Flipper Length')
g.set_ylabels('Body Mass')

Machine learning

You can also use the penguins dataset for training a machine learning model that can predict a penguin's species from its size measurements. load_penguins() will return a tuple (X,y) if you set return_X_y = True. Here, X includes only 4 size measurements variables and y corresponds to the species variable.

from sklearn.model_selection import train_test_split
from sklearn.pipeline import FeatureUnion, make_pipeline
from sklearn.metrics import confusion_matrix
### To deal with missing values
from sklearn.experimental import enable_iterative_imputer
from sklearn.impute import IterativeImputer
from sklearn.tree import DecisionTreeClassifier

X,y = load_penguins(return_X_y = True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=100,
                                            random_state=0)

imp = IterativeImputer(max_iter=10, random_state=0)
clf = make_pipeline(imp, DecisionTreeClassifier())
clf = clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
print(confusion_matrix(y_test,y_pred,labels=['Adelie','Chinstrap','Gentoo']))
array([[47,  1,  0],
       [ 3, 17,  0],
       [ 0,  0, 32]], dtype=int64)

print(clf.score(X_test,y_test))
0.96

License

Data are available by CC-0 license in accordance with the Palmer Station LTER Data Policy and the LTER Data Access Policy for Type I data.

Bibliography

Gorman KB, Williams TD, Fraser WR (2014) Ecological Sexual Dimorphism and Environmental Variability within a Community of Antarctic Penguins (Genus Pygoscelis). PLoS ONE 9(3): e90081. https://doi.org/10.1371/journal.pone.0090081

See also

More information about the dataset is available in its official documentation.

The Palmer penguins dataset in Julia: https://github.com/devmotion/PalmerPenguins.jl