import numpy as np
import pandas as pd

from lets_plot import *

LetsPlot.setup_html()

Function parallel_coordinates_plot()

def parallel_coordinates_plot(df: pd.DataFrame, class_column_name, order=None):
    plot_df = df.copy()
    plot_df.insert(0, 'par_plot_idx', list(range(df.shape[0])))

    var_names = df.columns.tolist()
    var_names.remove(class_column_name)

    plot_df = plot_df.melt(
        id_vars=[class_column_name, 'par_plot_idx'],
        value_vars= var_names
    )
    
    p = ggplot(plot_df, aes(x='variable', y='value', color=class_column_name, group='par_plot_idx')) \
        + geom_line(size=1)

    if order is not None:
        p += scale_x_discrete(breaks=order)
        
    return p

Demo

iris = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/iris.csv')
iris.head()

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa

Default plot

parallel_coordinates_plot(iris, 'species')

Reordered columns with the order parameter

parallel_coordinates_plot(iris, 'species', order=['petal_width', 'sepal_width', 'petal_length', 'sepal_length'])

See also:
https://r-graph-gallery.com/parallel-plot.html