import numpy as np
import pandas as pd
from lets_plot import *
LetsPlot.setup_html()
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
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 |
parallel_coordinates_plot(iris, 'species')
order parameter¶parallel_coordinates_plot(iris, 'species', order=['petal_width', 'sepal_width', 'petal_length', 'sepal_length'])