How to create a Datawrapper column chart
The column chart is a vertical variation of the bar chart. The strength of this chart type is that the user can see the values clearly and is able to compare wether the values went up or down or stayed the same.
The column chart will be your first choice in a lot of occasions. As you can see below it is possible in a Datawrapper column chart to display negative values (see value for 2009 below). A limitation of the column chart is the space to display legend on the x-axis. If you have a lot of values Datawrapper will try to turn them vertically, but this makes reading the chart much harder. When you have many values and longer names (e.g. all US states) switch to a bar chart in Datawrapper.
In this tutorial, you be guided through the steps to prepare and then upload your dataset into Datawrapper in order to create a column chart like the one below.
1. Preparing importing the data
For this example, we use a dataset about the world's total GDP growth. The table used for the chart above is formatted as follows.
Tipp: You can copy the data from this table & paste it directly into Datawrapper. Make sure that you copy all fields to make this work.
|Year/Region||World average||Advanced economies||Eurozone||Developing countries|
Source: Sample data
Note the structure of the dataset above:
- One header row consisting of different labels
- The first column defines the category
- The second and following columns define categorical dimensions
- Categorical dimensions consist of comparable values of the same measure
In this case, we use several categorical dimensions (World average, Advanced economies etc.). Datawrapper can transform these these into separate tabs. This leads to a more interactive chart as the reader can select different alternations of the chart by switching between tabs that you define in the column header.
One note of caution: In this tutorial we want to show all options. In standard cases consider to to create column charts with just one categorical dimension based on a dataset consisting of two columns overall. The reason for this: If you publish primarily to mobile screens try to avoid this interactive version, because only few users tend to click "sideways" to the other options. For mobile use and potentially even as a general rule it is advisable to create separate charts and stack them on a page for easy scrolling.
2. Check & Describe
This is what the table will look like after you uploaded it. Make sure that the box "First row as lable" is ticked so that Datawrapper correctly identifies categories and categorical dimensions.
Click on "Proceed" and Datawrapper will take you to the next step.
Once you're in the " Visualize" tab, choose " Column Chart" and Datawrapper will create a first iteration of your data. Continue with the steps refine, annotate, and design to finish your chart. We cover this in a separate short tutorial found here.