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Treemap Chart

Size nested rectangles by weight to show a portfolio's composition at a glance.

What is a treemap chart?

A treemap displays hierarchical or part-to-whole data as a set of nested rectangles, where each rectangle's area is proportional to its value. In finance it is a natural fit for portfolio composition: every holding becomes a tile sized by its weight, so the biggest positions dominate the picture and concentration is instantly visible. Unlike a pie chart, a treemap uses space efficiently and can nest categories within categories.

Portfolio Composition Treemaptreemap

Illustrative ten-position equity portfolio sized by weight. Values are for demonstration only.

A list of weights is hard to feel; a treemap makes composition visceral. The largest holdings command the largest tiles, so concentration and diversification jump out without reading a single percentage. This tool renders a ten-position equity portfolio as a treemap so you can see how weight translates into visual dominance.

Area encodes weight

The core principle of a treemap is that area equals value. A holding twice the weight of another gets twice the rectangle, so the layout is an honest map of where capital actually sits. This makes concentration risk obvious: if a handful of tiles swallow most of the canvas, the portfolio is far less diversified than a long holdings list might suggest. The human eye judges relative area quickly, which is the treemap's advantage over a table.

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Colour adds a second dimension for free. Tiles can be shaded by sector, by performance or by any secondary metric, letting a single chart show both how much is allocated where and how each slice is doing. A common pattern colours tiles green-to-red by daily return, producing the familiar market 'heat map' where size shows weight and colour shows the day's move.

Treemap versus pie chart

Both show part-to-whole composition, but the treemap scales far better. A pie chart becomes unreadable past a handful of slices and forces the eye to compare angles, which humans do poorly. A treemap packs dozens of holdings legibly, compares areas rather than angles, and — crucially — nests hierarchy, so you can drill from sectors down to individual names within the same view. For real portfolios it is usually the stronger choice.

How Quadesto computes it

Quadesto builds the treemap from a table of names and values, laying out rectangles by a squarified algorithm so tiles stay close to square and remain readable. You can add a category column to nest holdings under sectors and a metric column to drive tile colour. The portfolio above is rendered from a simple name-and-weight table, and the treemap embeds into allocation and holdings reports.

Build this with your own data

Upload a CSV or connect a live source, and Quadesto renders this exact chart — styled, computed, and embeddable in your reports and newsletters. Free to start.

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Frequently asked questions

What is a treemap chart used for?
It visualises part-to-whole and hierarchical data by sizing nested rectangles by value. In finance it is ideal for portfolio composition, sector weights and market maps, where tile area shows how much capital sits in each holding and concentration becomes immediately visible.
How do you read a treemap?
Each rectangle's area is proportional to its value, so larger tiles mean larger weights or amounts. Tiles may be grouped into categories and coloured by a second metric such as sector or return. Scan for a few dominant tiles to spot concentration, or many similar tiles for diversification.
Is a treemap better than a pie chart?
For more than a handful of categories, usually yes. Treemaps compare areas, which the eye reads better than the angles a pie relies on, and they stay legible with dozens of items. They also nest hierarchy, letting you show sectors and their holdings in one view — something a pie cannot do.
Can a treemap show hierarchy?
Yes. Treemaps nest rectangles within rectangles, so you can group individual holdings under sectors, or sectors under asset classes, and see both levels at once. This makes them well suited to portfolios and budgets where composition has natural layers.
Can I build a treemap from my own holdings?
Yes. Upload a table of names and weights to Quadesto, optionally add category and colour columns, and the engine lays out a squarified treemap. Nest by sector, colour by return, and embed the finished chart in allocation reports.