How to create a column chart
The column chart is a vertical variation of the bar chart. It works especially good for time series with only a few dates and for information typically shown with a column chart, e.g. election results in some countries.
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.
Preparing and importing the data
You can copy & paste data from Excel or the web, or upload your own CSV files. For example, here is the dataset for the election result chart up there. Your dataset should be formatted as following:
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.
Note the structure of the dataset above:
- The text in the header row won't be visible in the final chart. It's a good idea to include them anyway, to not forget what each column contains. (If you don't want to include the header row, make sure to uncheck the "First row as label" checkbox in the 2nd step, "Check & Describe".)
- The first column contains the labels of your columns, e.g. the party names.
- The second column contains the values that should be shown with the height of the columns, e.g. the election results.
Check & Describe
This is what the table will look like after you uploaded it. Make sure that the box "First row as label" 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 the 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.