How to create a long table (archived chart type)
If you want to show more than 20 rows of data, your best choice in Datawrapper is the Long Table. Check out the example below. It has quite a number of features, such as pagination and even a fast search. So consider the long table as an optional, additional piece of information, e.g. for rankings or detailed local election results. On occasion, a long table can be the main content of a post or article.
Keep in mind though that in order to enable fully responsiveness, the number of columns has some limits. A long table with >10 columns will be squeezed on a mobile screen, simply because of the dimensions of the screen. Should you have that much information the recommended solution is to break up the table into several tables or visualizations. Mobile users can sum up to 50 percent or more of your readers, for them (and for the desktop users as well) it is better to not overdo a table. Instead try to think of breaking up the information you got into pieces, which are easier to understand.
If you're not sure if you should use the Long Table or the Short Table, consult this article.
This guide will walk you through the steps to create an Long Table with Datawrapper:
The chart type to choose is the " Long Table". If you just started working with the tool note that the selection of the chart type will affect the options available in Refine, Annotate, and Design. We cover the options specifically for the long table in a separate short tutorial found here.
Preparing and importing the data
If you want to create this chart type, your data needs to be in a certain format. You'll need:
- One header row containing descriptive labels ("Model", "Base Price", etc.)
- At least two columns with categories, numeric values or dates
All the columns you upload will also be displayed in your table. Note that only columns with numeric values can be displayed with an "inline bar chart", as in the chart above.
Here are five rows of the data we used to create the chart at the top of the page. You can download the whole dataset directly from the table above. Click on "Download data" at the bottom of the Datawrapper table to receive a .csv, that you can then upload into Datawrapper.
Company Women earn x less
Share of men who received bonus pay
Share of women who received bonus pay Employer size ALDI STORES 6.9 5.6 5.1 5000 to 19,999 AMERICAN AIRLINES, INC. 9.2 34.2 8.3 5000 to 19,999 ARGOS 20 85 93 5000 to 19,999 ASDA STORES 37 95 91 5000 to 19,999 B & M RETAIL 0.8 21.9 33.8 5000 to 19,999
These numbers are percentages, but it's best to download them without the percentage signs. We will add percentage signs later.
Once you prepared your data, create a new chart in Datawrapper. You can do so by going to our homepage and clicking on "Create a chart". In Step 1: Upload, copy & paste your dataset, upload it as a .csv or an Excel sheet. It will look like this:
Click "Proceed" at the bottom right to go to the next step:
Check & Describe
In the second step, you can check if your dataset was imported correctly and make changes to it - if necessary. If you did not upload a header row, you have to untick "First row as label" to avoid losing your first row of data. Always remember to do this if you don't have descriptive row and column headers.
In step 2, your data looks like this. You can see that Datawrapper correctly recognized your numbers as numbers (and not as text or dates) because they are colored in blue and are right-alined. To learn more about the Datawrapper's automatic recognition of data formats, visit this article.
(This screenshot doesn't show the full dataset – the first column is so big that the table become scrollable.)
Click on a table header to get to the "Edit column" menu, which lets you add percentage signs:
Click on "Proceed" at the bottom left to go to Step 3: Visualize:
In this step, you see a first chart. It's probably a line chart. We want to change that. To do so, click on the "Long Table" symbol in the grid of available chart types:You will now see a long table, without a title, descriptions or customized colors. Maybe you want to further refine, annotate & define this chart. We cover this in a separate short tutorial found here.