Customizing your stacked column chart
This article describes how to customize a stacked column chart in Datawrapper. We assume that you have already uploaded your dataset into Datawrapper and selected the stacked column chart as your visualization of choice.
We will go through three tabs in step 3: Visualize to do so: " Refine", "Annotate" & "Design". (In the "Refine" and "Annotate" tab, you can resize the chart, to make it wider or taller. To do so, click, hold, and drag the arrow in the lower right corner to scale the chart window.)
After clicking on the "Refine" tab, the first thing option at your disposal is to specify the values that you want to appear on the vertical and horizontal axis. You have different features available under each axis to customize the appearance of these axes.
For the vertical axis, you can modify:
- custom range: allows you to set your own minimum and maximum values. However, please note that the vertical axis of column chart has been set, by default, to start at zero, meaning that you can only modify the maximum value on this axis.
- show grid lines: depending on whether or not you want to highlight the display of certain values, you can choose to enable or disable this feature
- show axis labels: with the first setting ''Number format'', you can decide how to show your values. Below are three examples but there are many different formats available and choice of a format ultimately depends on how big or small your values are:
- Choose the number format "123.4k" if you have big numbers like "1,303,428" that you'd rather want to display as "1.3m"
- Choose the number format "0.0" if you have very detailed numbers like "0.1922302" that you'd rather want to display as "0.2"
- Choose the number format "0%" or "0.0%" if you have a number that is a relative number, like in our case. This setting will add a percentage sign.
For the horizontal axis, you can:
- sort columns: here you have two settings; sort columns automatically or in reverse order. If you enable the automatic setting, your columns will be arranged in descending order and reversing the order would naturally sort them in ascending order.
- rotate labels: this handy little setting allows you to rotate the labels of your individual columns, in case some of the labels are too long to fit together in a horizontal fashion. Here again, you have the choice to set the rotate option on ''auto'', ''always'' or ''never''.
- In the next panel, "Appearance", you can modify three settings:
- Customize color. This allows you to change the color of columns either based on one base color whose gradient you can change across different stacks or by using different colors for different stacks.
- Show or hide value labels. By default, Datawrapper only shows the value labels on the bars if readers hover on them. But you can choose to disable that and always show the value labels.
- Category labels. This offers you to show the labels two ways: direct or color key. In the direct option, you can show the labels for individual stacks next to them whereas using the color key will show the labels at the top of the chart in the form of a key.
If you've created a Datawrapper chart or map before, you already know this feature. Here we can give your chart a title, a description, add notes and a source:
- We recommend using the title to tell your readers the most interesting aspect about this chart – the one key statement that you want your readers to remember from this chart, e.g. "Unemployment highest in the south"
- The description should have as much information about the data as possible: What do we see exactly? E.g. "Unemployment rates in % in all US states, 2016"
- Think of notes as footnotes, where we want to clarify any abnormalities about your data. E.g. "California unemployment rates from Jan and Feb 2016 not included in the calculation."
- The source name will give our readers the information about how trustworthy our data is. Does it come from a government institution or another trustworthy organization? The source URL lets our reader dig even deeper and have a look at the underlying data. Whenever possible, ensure that you provide a source name and source URL for every map or chart to increase transparency. E.g. US Bureau of Labour Statistics, August 2017
In the 2nd panel in the "Annotate" tab, we can emphasize certain variables. To do so, select the element(s) you want to highlight. The rest of the bars will automatically tone down:
In the ''Design'' tab under step 3: Visualize, you can select a preset layout and enable social sharing function to share your work. Users of the Free plan have two options: one layout with and one without the "Get the data" link. Users of Datawrapper's Custom and Enterprise plan have the option to select a custom layout here. The output locale option allows you to choose in which format do you want the decimals, 1000 separators and dates to appear in your visualization.
In the final step 4: Publish & Embed, you have the option to publish the chart either by sharing the URL or by copying the embed code directly on your website or CMS (recommended). You can also download your chart as a PNG (available to all users regardless of the type of subscription plan they have) or a PDF (available only to users of Custom and Enterprise plan). For more information on the different pricing plans, click here.