plot_event_parallel_coordinates()

plot_event_parallel_coordinates() draws event sequences as parallel-coordinate-style trajectories.

This function is Sequenzo's closest counterpart to TraMineR seqpcplot-style visualization.

Function Usage

plot_event_parallel_coordinates(
    event_sequences,
    group_labels=None,
    color_palette=None,
    event_labels_order=None,
    order_align="first",
    title="auto",
    x_label=None,
    y_label=None,
    rows=1,
    cols=None,
    figsize=(12, 8),
    linewidth=3.0,
    alpha=0.45,
    fontsize=11,
    save_as=None,
    dpi=200,
    show=False
)

Entry Parameters

Parameter	Required	Type	Description
event_sequences	✓	EventSequenceData / EventSequenceList	The full event-sequence dataset to plot.
group_labels	✗	array-like	Optional grouping variable for faceted panels.
event_labels_order	✗	Sequence[str]	Optional custom display order for event labels.
order_align	✗	str	Horizontal axis mode: event order position ("first", "last") or timestamps ("time").
x_label, y_label	✗	str	Axis label overrides.
save_as	✗	str	Save path; .png is auto-appended if missing.
dpi	✗	int	Save resolution (default 200).
show	✗	bool	If True, calls plt.show() inside the function.

TraMineR Parameter Mapping

• event_sequences -> TraMineR event-sequence object / seqelist
• group_labels -> TraMineR group
• color_palette -> TraMineR cpal
• event_labels_order -> TraMineR alphabet
• title -> TraMineR main
• x_label / y_label -> TraMineR xlab / ylab

What It Does

• Displays event order position on the x-axis and event categories on the y-axis.
• Aggregates identical trajectories and renders weighted visual emphasis.
• Supports grouped panels for side-by-side comparison.

Example (Step by Step)

from sequenzo.event_sequences import plot_event_parallel_coordinates

# Step 1: Plot all sequences
plot_event_parallel_coordinates(
    event_sequences=eseq,
    title="Event sequences (all cases)",
    x_label="Position",
    y_label="Event",
    save_as="outputs/event_parallel_all",
    dpi=300,
    show=True
)

# Step 2: Plot by group
plot_event_parallel_coordinates(
    event_sequences=eseq,
    group_labels=df["sex"],
    title="Event sequences by sex",
    x_label="Position",
    y_label="Event",
    save_as="outputs/event_parallel_by_sex",
    dpi=300,
    show=True
)

R Counterpart

• Closest R function: seqpcplot / plot.seqelist(type="pc")
• Mapping note: Visual intent is similar, but panel layout and styling are not one-to-one.

Authors

Code: Yuqi Liang

Documentation: Yuqi Liang

Reference

Ritschard, G., Bürgin, R., & Studer, M. (2013). Exploratory Mining of Life Event Histories. In J. J. McArdle & G. Ritschard (Eds.), Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences (pp. 221–253). Routledge.