What is it for?
color areas of your map based on numerical or categorical data. This is known as a choropleth map.
Creating a choropleth map can be very useful if you need to:
- Visualize data in a predetermined geographic area.
- Display a value’s distribution/variability across a region.
In this article
How to get started
TIP: Struggling to find the right regions for your map? Check out our GeoJSON repository where we've sourced, checked, and resized various region files ready for you to download and use in Flourish.
WARNING: Once you upload your data, make sure that the column bound under the Geo region key is the correct one – and that the same column exists in the Regions geometry tab, too.
Customizing your choropleth mapAfter importing your data, you can then focus on customizing your visualization. The shading of the map will depend on whether your values are categorical or numeric.
Coloring your regions based on numerical data
Numerical data usually refers to data that displays some numeric relationship, for example, temperature variations, population numbers, or percentages.
Flourish sets the default scale type as categorical, however, you can change this by opening the Regions layer settings and switching to Numeric instead.
By choosing the Numeric scale type, you can also select a sequential or diverging legend, as well as choosing a linear or binned coloring.
- A sequential palette ranges between two colors (typically having one “main” color) ranging from white or a lighter shade to a darker one, by varying one or more of the parameters in the HSV/HSL color space.
- A diverging palette ranges between three or more colors, usually between two contrasting colors at either end with a neutral color or white in the middle separating the two. Diverging palettes should only be used when there is a value of importance around which the data are to be compared or a natural middle to the data. This could be to mark whether something is positive or negative or whether some values are below or above a specific threshold, for example.
In addition, when using binned or linear coloring, you can manually set bins or thresholds for your colors and your legend. Learn more about this here.
- A linear scale will create a smooth gradient between the two colors bound to the minimum and maximum values.
- A binned scale will split the colors into containers (bins) and will map each bin into a range of the data. You can create equally-sized bins or not depending on the distribution of your data.
Coloring your regions based on categorical data
Categorical data usually represents data that can be split into groups, such as race, gender, or election results. The process of shading your map's regions categorically is very simple. After adding a column with categories to the Values binding, the template will apply a categorical palette to your map by default. So, in this case, you just need to leave the settings as they are.
You can further customize the your color palette and the look of your regions by adding color overrides as shown in this help doc.
You can also use categorical coloring to show custom bins within your data. Read our help doc to learn how to do this.