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.
pip install palmerpenguinsSize 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.
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')
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))
0.96Data 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.
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
More information about the dataset is available in its official documentation.
The Palmer penguins dataset in Julia: https://github.com/devmotion/PalmerPenguins.jl
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