table

Groups data by two fields and lays the groups out in a 2D grid — one axis per field. The primary operator for heatmaps and other grid-based visualizations.

from gofish import chart, table, rect, gradient

chart(data, color=gradient(["#ffffcc", "#fd8d3c", "#bd0026"])).flow(
    table(by={"x": "hour", "y": "day"}, spacing=4)
).mark(rect(fill="value")).render(w=500, h=300, axes=True)

Signature

table(*, by, **options) -> Operator

Parameters

Parameter	Type	Description
by	dict	A dict with x and y keys naming the two fields
spacing	int | tuple[int, int]	Gap between cells — a single number or (x_spacing, y_spacing)
numCols	int	Override the inferred column count

Returns an Operator for use inside .flow().

Examples

# Heatmap: hour on x, day on y, colored by value
chart(data, color=gradient(["#ffffcc", "#fd8d3c", "#bd0026"])).flow(
    table(by={"x": "hour", "y": "day"}, spacing=4)
).mark(rect(fill="value"))

# Asymmetric spacing
chart(data).flow(table(by={"x": "col", "y": "row"}, spacing=(2, 8)))

Notes

• Data insertion order determines column and row ordering. Sort your data first if you need a specific order.
• Unlike nested spread calls, table exposes ordinal axes on both dimensions, so axis labels render on x and y.
• Pair gradient() on the chart color option with fill="fieldName" on the mark for heatmap coloring.