Treemap

A template from creating treemaps for visualising hierarchical data

Updated 6 years ago by Duncan Clark

How to use this template

This template is great for summarising your data across different categories and showing the result as a set of nested rectangles. (You can think of this template as a visual pivot table.)

Data requirements

The data should be in 'long-form' i.e. each row represents a single data-point and each column represents a variable. For example:

Film                     Genre      Studio         Worldwide Gross ($m)
27 Dresses               Comedy     Fox            160.31
(500) Days of Summer     Comedy     Fox            60.72
A Dangerous Method       Drama      Independent    8.97
A Serious Man            Drama      Universal      30.68
Across the Universe      Romance    Independent    29.37
Beginners                Comedy     Independent    14.31
Dear John                Drama      Sony           114.97

Usage

Columns can be seen as either categorical (e.g. Genre and Studio) or numeric (e.g. Worldwide Gross).

Choose:

  • categorical columns to nest your data by
  • numeric columns to size the rectangles by

For example, if we wanted to know which studio took the most revenue we could nest by Studio and size by Worldwide Gross.

If we wanted to further break down each studio into genres, we could nest by Studio and Genre.

If 2 or more columns are chosen to nest you'll be able to zoom into a category by clicking. Zoom out by clicking the triangle that appears in the top right of the chart.

Examples

Tips

  • You don't have to choose a column to size by, in which case the rectangles will be size by the count of data points.
  • Click on the popup to freeze it. Click on it again to unfreeze.
  • You can choose the number of visible hierachy levels. Try varying this within a story to gradually break down categories into sub-categories.

Credits

Created by Peter Cook and the Flourish team.

This section documents API usage specific to this template, so for an introduction we suggest you refer to the generic API documentation instead.

template: _603

version: _16

Template data

There are three different formats in which you can supply data to this template. The most convenient for you to use likely depends on the source of your data, as described below.

1. Array of arrays, and a bindings object

You can supply arrays of arrays to opts.data, which might look like:

{
    data: {
        data: [
            [ "DataColumn1Value1", "DataColumn2Value1",
            [ "DataColumn1Value2", "DataColumn2Value2",
            [ "DataColumn1Value3", "DataColumn2Value3",
            ...
        ]
    }
}

where each array of arrays represents the rows in a data sheet.

To tell the API how the values from each column should be associated with the keys that the template is expecting, you must also supply an object attached to opts.bindings. (The meanings of the keys in the bindings object are documented below.) The minimal bindings you can supply for this template are as shown in this example:

{
    template: "_603",
    version: "_16",
    bindings: {
        data: {
            
        }
    },
    data: {
        data: [
            [ "DataColumn1Value1", "DataColumn2Value1",
            [ "DataColumn1Value2", "DataColumn2Value2",
            [ "DataColumn1Value3", "DataColumn2Value3",
            ...
        ]
    }
}

All possible bindings that you can supply are shown in this example:

{
    template: "_603",
    version: "_16",
    bindings: {
        data: {
            nest_columns: [0, 1, ...], // index(es) of column(s) in your data
            size_column: 2, // index of a column in your data
            filter: 3, // index of a column in your data
        }
    },
    data: {
        data: [
            [ "DataColumn1Value1", "DataColumn2Value1",
            [ "DataColumn1Value2", "DataColumn2Value2",
            [ "DataColumn1Value3", "DataColumn2Value3",
            ...
        ]
    }
}

2. Array of objects with arbitrary keys, and a bindings object

This format is most likely useful when you have data from an external source, such as CSV data loaded from d3-dsv. You should supply this attached to the opts.data, which might look like:

{
        data: [
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            ...
        ]
    }

... but with the keys being the column headers from your source data instead. You must also supply an object attached to opts.bindings. The minimal bindings you can supply for this template are as shown in this example:

{
    template: "_603",
    version: "_16",
    bindings: {
        data: {
            
        }
    },
    data: {
        data: [
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            ...
        ]
    }
}

All possible bindings that you can supply are shown in this example:

{
    template: "_603",
    version: "_16",
    bindings: {
        data: {
            nest_columns: ["DataHeader1", "DataHeader2", ...],
            size_column: "DataHeader3",
            filter: "DataHeader4",
        }
    },
    data: {
        data: [
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            { "DataHeader1": ..., "DataHeader2": ..., ... },
            ...
        ]
    }
}

(As before, the keys containing "Header" would be replaced by column names from your data source.)

3. Array of objects with template-defined keys

There is an alternative format you can use, which is likely to be easier to use if your data is not from a spreadsheet source. With this alternative format you supply your data to the template as an array of objects, attached to opts.data, where the keys must be those used by the template, as documented below. In this case there is no need to supply a bindings object, since the key names are already those expected by the template. The required properties in the data object are as follows (scroll down for a description of what each property is):

{
    template: "_603",
    version: "_16",
    data: {
    data: [
        {
            nest_columns: [...]
        },
        ...
    ]
},
    ...
}

And the full list of all possible properties is as follows:

{
    template: "_603",
    version: "_16",
    data: {
    data: [
        {
            nest_columns: [...],
            size_column: ...,
            filter: ...
        },
        ...
    ]
},
    ...
}

Meanings of the template data keys:

  • data.nest_columns: nest_columns
  • data.size_column: size_column
  • data.filter: filter

Template settings

Options for opts.state.

header_title string

Title.

header_subtitle string

Subtitle.

header_color color

Color.

header_align string

Alignment.

Allowed values:

  • left (fa-align-left)
  • center (fa-align-center)
  • right (fa-align-right)

header_margin number

Margin.

header_margin_advanced boolean

Advanced margin settings.

header_margin_top number

Top.

header_margin_right number

Right.

header_margin_bottom number

Bottom.

header_margin_left number

Left.

filter_type string

Control type.

Allowed values:

  • auto (Auto)
  • dropdown (Dropdown menu)
  • slider (Slider)
  • grouped-buttons (Button group)
  • floating-buttons (Buttons)

filter_width number

Width.

controls_padding number

Margin.

filter_include_all boolean

Include “All” option.

filter_all_label string

“All” label.

Treemap

palette string

Colour scheme or custom colours. Choose from the list or enter a custom palette as a comma-separated list of colour codes or names (e.g. red, #343434)

Allowed values:

  • flourish_default_1 (Flourish categories A)
  • flourish_default_2 (Flourish categories B)
  • carto_pastel (Pastel light)
  • carto_antique (Pastel dark)
  • carto_rainbow (Rainbow)
  • schemeCategory20 (20 colours (paired))

aggregation_type string

Size cells by.

Allowed values:

  • Sum (Sum)
  • Count (Count)

treemap_type string

Layout mode.

Allowed values:

  • treemapBinary (Best shapes)
  • treemapResquarify (Best for animations)
  • treemapSlice (Horizontal)
  • treemapDice (Vertical)
  • treemapSliceDice (Horizontal then Vertical)

treemap_ratio number

Ratio.

cellPadding string

Padding. Add padding between hierarchy levels

Allowed values:

  • low (Thin)
  • medium (Medium)
  • high (Thick)

num_of_visible_levels number

Visible Levels. How many hierarchy levels are visible at once?

Min: 1

Popups

show_popups boolean

Show popups.

Text colour.

Fill colour.

Fill opacity.

Title separator.

Font size.

Min: 1

Prefix.

Decimal places.

Suffix.

Animations

animation_duration number

Duration. In seconds