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Hexbin Plot Maker

Hexagonal Density Chart from x,y Points, Download SVG or PNG Free

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How the Hexbin Plot Maker works

This hexbin plot maker bins dense scatter data into hexagons. A scatter plot with thousands of points turns into a solid blob where the interesting detail is. A hexbin plot fixes that by tiling the plane with hexagons and shading each one by how many points land inside it, so dense regions show up as dark cells and sparse ones as pale, with the empty parts left blank. Paste two columns of numbers, pick a hexagon size, and download the chart as SVG or PNG. Nothing is uploaded.

Hexbin plot maker: what to paste

Two numeric columns, x then y, one point per row, separated by commas or tabs. A header row is used for the axis labels when present and skipped otherwise. Extra columns are ignored, and rows where either value is missing or not a number are dropped. The chart is meant for large sets; a few dozen points still bin correctly but a scatter plot would say more.

How the binning works

The plot area is covered with a regular hexagonal grid and each point is assigned to the hexagon whose centre is nearest, the same method as R's hexbin package and matplotlib's hexbin. Hexagons are used rather than squares because every neighbour is the same distance away, which gives smoother, less blocky density and avoids the visual bias of a square grid's diagonals. The hexagon size sets the resolution: Small shows fine structure but looks speckled with modest data, Large smooths everything into broad regions. Medium is a sensible start; change it and see which view tells the story honestly. Empty hexagons are not drawn, so the overall shape of the data stays visible.

Colour and count scale

Each hexagon's shade is its count mapped onto the chosen colour scale, from the palest tone for one point to the darkest for the fullest cell; the legend in the corner shows that range and the top count. With Linear scaling, a single very dense cluster can leave the rest of the chart almost white. Log scaling compresses the counts so that cells with 2, 20 and 200 points are clearly distinct, which is usually the better choice for skewed data such as prices, response times or anything with a long tail. Hover a hexagon for its exact count and approximate centre.

Reading the chart

Dark cells are where the data concentrates. Several separate dark regions suggest distinct groups in the data, a diagonal ridge suggests correlation, and a ring or crescent means the relationship is not a straight line. The stats panel gives the number of points, the number of occupied hexagons, the location of the densest one and the average points per hexagon, a quick check on whether the size is too fine or too coarse.

Exporting

Download SVG gives a vector file with one path per hexagon and editable text. Download PNG renders at one, two or three times the preview width. Copy SVG puts the markup on the clipboard.

FAQ

Hexbin or scatter plot?

Under a few hundred points, a scatter plot shows every observation and nothing is hidden. Above that, points overlap and the eye cannot judge density; a hexbin restores that information. Many analysts use both: the scatter to spot outliers, the hexbin to see the bulk.

Why do the hexagons at the edge look cut off?

The hexagon grid is clipped to the plot area so the axes line up with the data. A cell that straddles the border still counts every point inside it; only its drawing is trimmed.

Can I plot a third value instead of a count?

Not on this page; each hexagon shows how many points it holds. For a chart where a third column sets the colour, use the bubble chart maker, or the heatmap maker if the data is already aggregated into a grid.

How many points can it handle?

Tens of thousands bin in well under a second in a normal browser, and the output stays small because only the hexagons are drawn, not the points. The paste box is the practical limit.

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