Plotynium is a Data Visualization framework for Python, inspired by Observable Plot.
pip install plotynium
import polars as pl
from sklearn.datasets import load_digits
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
import plotynium as ply
mnist = load_digits()
scaler = StandardScaler()
X_scaled = scaler.fit_transform(mnist.data)
pca = PCA(n_components=2)
components = pca.fit_transform(X_scaled)
# Prepare your data with Polars, Pandas or manually
df = pl.DataFrame(components, schema=["Component 1", "Component 2"])
df = df.insert_column(2, pl.Series("digit", mnist.target))
plot = ply.plot(
marks=[
ply.dot(
df.to_dicts(),
x="Component 1",
y="Component 2",
stroke="digit",
symbol="digit",
)
],
color={"scheme": ply.Interpolation.RAINBOW},
symbol={"legend": True},
style={"background": "#0d1117", "color": "#e6edf3"},
)
with open("pca.svg", "w") as file:
file.write(str(plot))