parallel_coordinates(frame, class_column, cols=None, ax=None, color=None, use_columns=False, xticks=None, colormap=None, axvlines=True, axvlines_kwds=None, sort_labels=False, **kwargs)
Column name containing class names.
A list of column names to use.
Matplotlib axis object.
Colors to use for the different classes.
If true, columns will be used as xticks.
A list of values to use for xticks.
Colormap to use for line colors.
If true, vertical lines will be added at each xtick.
Options to be passed to axvline method for vertical lines.
Sort class_column labels, useful when assigning colors.
Options to pass to matplotlib plotting method.
Parallel coordinates plotting.
.. plot::
('context', 'close-figs')
>>> df = pd.read_csv(
... 'https://raw.github.com/pandas-dev/'
... 'pandas/main/pandas/tests/io/data/csv/iris.csv'
... )
>>> pd.plotting.parallel_coordinates(
... df, 'Name', color=('#556270', '#4ECDC4', '#C7F464')
... )
<AxesSubplot:xlabel='y(t)', ylabel='y(t + 1)'>Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them