Density Plot¶

2D kernel density estimation — shows where points concentrate.

When to Use¶

Visualizing point concentration (city events, species observations)
When scatter plots are too dense to read
Combining density visualization with point overlay

Example¶

from d3_bridge import DensityPlot

chart = DensityPlot(
    data=Observation.objects.values("longitude", "latitude"),
    x="longitude",
    y="latitude",
    bandwidth=25,
    title="Observation Density",
)

With Point Overlay¶

chart = DensityPlot(
    data=data,
    x="x", y="y",
    show_points=True,
    point_radius=2,
    point_opacity=0.3,
)

Bandwidth¶

Controls the smoothing. Lower = more detail, higher = smoother:

chart = DensityPlot(data=data, x="x", y="y", bandwidth=10)   # detailed
chart = DensityPlot(data=data, x="x", y="y", bandwidth=50)   # smooth

Parameters¶

Parameter	Type	Default	Description
`x`	str	—	X-axis field
`y`	str	—	Y-axis field
`bandwidth`	float	`20`	Kernel bandwidth (smoothing)
`thresholds`	int	`20`	Number of density levels
`color_scale`	str	`"sequential"`	Color scale type
`grid`	bool	`True`	Show axes grid
`show_points`	bool	`False`	Overlay scatter points
`point_radius`	float	`2`	Point radius
`point_opacity`	float	`0.3`	Point opacity
`x_label`	str	`None`	X-axis label
`y_label`	str	`None`	Y-axis label