pt.grid / | / attachments

Coordinates & layout

Minimal call

import math
xs = [i * 0.2 for i in range(40)]
signal = {"x": xs, "y": [math.sin(x) for x in xs]}
counts = {"cat": ["a", "b", "c"], "n": [4, 7, 3]}
values = {"x": [0.1, 0.4, 0.5, 0.55, 0.7, 0.8, 0.9, 1.1, 1.3]}

a = pt.chart(signal, aes(x="x", y="y"), title="signal",
             data_width=200, data_height=130)
a.add_line()
b = pt.chart(counts, aes(x="cat", y="n"), title="counts",
             data_width=200, data_height=130)
b.add_bar()
d = pt.chart(values, aes(x="x"), title="dist",
             data_width=200, data_height=130)
d.add_hist(bins=6)
c = pt.grid([[a, b], [d, None]])

Docstring

Build a grid-layout `Layout` from a list-of-lists of cells.

    Each cell is either a `Chart` or `None` (empty). All rows must have
    the same number of columns. The grid does **no proportional
    redistribution** — each column's width is the max natural canvas
    width across cells in that column; each row's height is the max
    natural canvas height across cells in that row. To make a column
    twice as wide as another, set `data_width=` directly on the leaf
    charts; the grid then sums their natural canvases plus per-boundary
    gaps.

    The constructor takes only the structural argument (`cells`); all
    behavior knobs live on methods so they compose uniformly across
    grid-built and `|`/`/`-built layouts. For inter-panel gap, chain
    `.gap(N)` for a unified value or `.gap(x=..., y=...)` for per-axis
    control. For axis sharing, chain `.share_x("col"/"row"/"all")` /
    `.share_y(...)`.