Parallel Coordinates Plot#

A parallel coordinates plot of 4 features of the penguins dataset to analyze how they are related with the species. We can see, for instance, that Gentoo penguins dominate the flipper_length_mm feature, having the highest flipper lengths.

import hvplot
import pandas as pd
from sklearn.preprocessing import MinMaxScaler

df = hvplot.sampledata.penguins("pandas")
df_scaled = df
cols = ["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
scaler = MinMaxScaler()
scaled_features = scaler.fit_transform(df[cols])
df_scaled = pd.DataFrame(scaled_features, columns=cols)
df_scaled["species"] = df["species"]

hvplot.plotting.parallel_coordinates(
    df_scaled,
    class_column="species",
    title="Parallel Coordinates Plot (Bokeh)",
)

import hvplot
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
hvplot.extension("matplotlib")

df = hvplot.sampledata.penguins("pandas")
df_scaled = df
cols = ["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
scaler = MinMaxScaler()
scaled_features = scaler.fit_transform(df[cols])
df_scaled = pd.DataFrame(scaled_features, columns=cols)
df_scaled["species"] = df["species"]

hvplot.plotting.parallel_coordinates(
    df_scaled,
    class_column="species",
    title="Parallel Coordinates Plot (Matplotlib)",
)