Example: Penguin Body Mass Analysis

SAMPLE PROJECT. Replace with your own work. Shows the expected structure.
Python
Polars
Data Visualization
Published

January 1, 2026

Note

This is a sample project page. Delete the example: true line when you replace it with your own work.

The problem

One or two sentences. Who needed an answer, and what was the question? Example: Which penguin species is heaviest, and does flipper length predict body mass?

My approach

What did you do, and why that way? Name the tools and the choices you made.

The work

import polars as pl
from lets_plot import *
LetsPlot.setup_html()
pl.Config.set_tbl_hide_dataframe_shape(True)  # hides the "shape: (3, 2)" line above tables

df = pl.DataFrame({
    "species": ["Adelie", "Chinstrap", "Gentoo"] * 3,
    "body_mass_g": [3700, 3730, 5076, 3680, 3790, 5000, 3720, 3750, 5100],
})
summary = df.group_by("species").agg(pl.col("body_mass_g").mean().round(0)).sort("species")
summary
species body_mass_g
str f64
"Adelie" 3700.0
"Chinstrap" 3757.0
"Gentoo" 5059.0 
(ggplot(summary, aes("species", "body_mass_g", fill="species"))
 + geom_bar(stat="identity")
 + labs(title="Mean body mass by species (sample data)"))

The result

What did you find or build? Use a number. Example: Gentoo penguins average about 5,000 g, roughly 35% heavier than the other species.

What I learned

One honest paragraph about what was hard and what you would do differently.