Step Sankey
Displays a step-by-step Sankey diagram showing which events users experience at each ordinal position in their path. The horizontal axis represents step number, making it easy to see how paths diverge over time.
Each column sums to 1 in standard mode, while in diff mode columns sum to 0.
Step Sankey and Step Matrix visualise the same underlying data in different forms: Step Sankey as a flow diagram, Step Matrix as a heatmap table. Use whichever makes the pattern you are looking for easier to spot.
Usage
stream.step_sankey(max_steps=15, path_pattern="add_to_cart->.*->purchase")
stream.step_sankey(diff=("country", "US", "<REST>"))
Parameters
Data
Data parameters change the computed result. They are exactly the arguments of
the widget's headless twin stream.step_sankey_data() — see
headless mode below.
| Parameter | Type | Description |
|---|---|---|
max_steps | int, default 10 | Number of path steps to compute. |
diff | tuple or list, optional | Draws a comparative chart for a pair of segments; see Diff mode. (segment_col, value1, value2) or (path_ids1, path_ids2); value2 may be <REST>. |
path_col | str, optional | Path ID column override; defaults to schema.path_col. |
path_pattern | str, optional | Same syntax as step_matrix's path_pattern. |
Display
Display parameters only affect how the widget is rendered.
| Parameter | Type | Description |
|---|---|---|
step_window | int, default 3 | Number of step columns shown around each anchor. |
height | int, default 500 | Widget height in pixels. |
sidebar_open | bool, default True | Whether the sidebar starts open. |
state_file | str, optional | JSON file the widget state is bound to; see Saving widget state. |
Headless mode
stream.step_sankey_data()
Compute per-step event-share matrices for Step Matrix / Step Sankey (headless).
Both widgets render the same underlying data — Step Matrix as a heatmap, Step Sankey as a flow diagram.
Examples
Basic
stream.step_sankey()Path pattern - central event
A single event as path_pattern re-centers the diagram on that event instead of
path_start: column 0 is always purchase, negative columns are the steps leading up
stream.step_sankey(path_pattern="purchase")Path pattern - funnel patterns
Chaining several anchors with .* renders one diagram block per anchor, side by side,
so you can follow a multi-step funnel across blocks.
stream.step_sankey(path_pattern="payment_details->.*->shipping_details->.*->purchase", step_window=2)Path pattern - drop-off points
path_pattern="path_end" centers on where paths end, so the columns to the left show
what users tend to do right before dropping off (or completing their path).
stream.step_sankey(path_pattern="path_end")Diff mode
stream.step_sankey(diff=["platform", "mobile", "desktop"])