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Quick Start

A standalone layer

Any layer displays itself — no explicit map setup needed:

import deckgl_marimo as dgl

layer = dgl.ScatterplotLayer(
    data=df,                                # pandas / polars / list of dicts / ...
    get_position=["longitude", "latitude"], # column names
    get_fill_color=[255, 140, 0],           # constant RGBA
    get_radius="population",                # per-row column
    radius_scale=10,
)
widget = layer.as_widget()
widget

as_widget() wraps the layer in marimo.ui.anywidget, giving you reactive .value access to viewport and pick state.

A multi-layer map

m = dgl.Map(
    layers=[
        dgl.ScatterplotLayer(
            data=cities_df,
            get_position=["lon", "lat"],
            get_fill_color=[255, 140, 0],
            radius_min_pixels=3,
        ),
        dgl.ArcLayer(
            data=flights_df,
            get_source_position=["src_lon", "src_lat"],
            get_target_position=["dst_lon", "dst_lat"],
        ),
    ],
    basemap="dark-matter",
    center=(-98.5, 39.8),
    zoom=4,
    pitch=45,
)
widget = m.as_widget()
widget

Accessors

Every get_* parameter accepts:

  • a constant — [255, 0, 0], 5.0
  • a column name — "population"
  • a list of columns for vectors — ["lon", "lat"]
  • a callable — lambda row: [row["v"], 0, 0, 255]
  • a ColorScale (color accessors only)

Fitting the view to data

m.fit_bounds(dgl.compute_bounds(df, position=["lon", "lat"]), padding=40)

Next steps