When should I use a density plot?

Showing distribution shape smoothly ● Comparing overlapping distributions

When should I avoid a density plot?

Discrete data ● When exact counts matter (use histogram)

What are common mistakes with density plots?

Wrong bandwidth selection ● Ignoring edge effects

Distribution

Density Plot

Smooth continuous estimate of a distribution using kernel density estimation.

Session Duration Distribution

Kernel density estimate (minutes)

View data (30 rows)

Chart data table: Session Duration Distribution
Duration
8
10
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Make a density plot with your data

Use a density plot when…

Showing distribution shape smoothly
Comparing overlapping distributions

Avoid when…

Discrete data
When exact counts matter (use histogram)

Data it needs

Property	Value
Min Rows	10
Min Columns	1
Column Types	number

Visual anatomy

Marks

area

Channels

position-xheight (density)

Axes

x-quantitativey-density

Guiding principles

PerceptionThe Encoding Hierarchy
Smooth curve reveals underlying distribution shape
IntegrityZero Baselines
Bandwidth controls smoothness — too wide hides modes, too narrow adds noise; Silverman's or Scott's rules of thumb are good defaults

Consider instead

Histogram

When exact bin counts matter

Common mistakes

Wrong bandwidth selection
Ignoring edge effects

History

Based on kernel density estimation developed by Rosenblatt (1956) and Parzen (1962).

Accessibility notes

Provide a quartile / peak summary table (min, Q1, median, Q3, max, mode) as text — generic 'summary statistics' alone leaves screen-reader users without the shape information the curve carries.

Got data? Let's see what works.

Drop your CSV. You'll get a Density Plot plus four alternatives - ranked by which one actually fits your data best.

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