Model

Code

from palmerpenguins import penguins
from pandas import get_dummies
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn import preprocessing

C:\Users\sshea\Documents\RStudio\DevOps-Exercises\Lesson1py\.venv\Lib\site-packages\palmerpenguins\penguins.py:2: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources

Get Data

Code

df = penguins.load_penguins().dropna()

df.head(3)

	species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
0	Adelie	Torgersen	39.1	18.7	181.0	3750.0	male	2007
1	Adelie	Torgersen	39.5	17.4	186.0	3800.0	female	2007
2	Adelie	Torgersen	40.3	18.0	195.0	3250.0	female	2007

Define Model and Fit

Code

X = get_dummies(df[['bill_length_mm', 'species', 'sex']], drop_first = True)
y = df['body_mass_g']

model = LinearRegression().fit(X, y)

Get some information

Code

print(f"R^2 {model.score(X,y)}")
print(f"Intercept {model.intercept_}")
print(f"Columns {X.columns}")
print(f"Coefficients {model.coef_}")

R^2 0.8555368759537614
Intercept 2169.2697209393996
Columns Index(['bill_length_mm', 'species_Chinstrap', 'species_Gentoo', 'sex_male'], dtype='object')
Coefficients [  32.53688677 -298.76553447 1094.86739145  547.36692408]