Customizing your range plot

After importing the data for your range plot, you can refine, annotate, and design your range plot in step 3: Visualize. In this tutorial, we'll walk you through all these steps to create the following chart:



In any tab of step 3: Visualize, you can click, hold, and drag the arrow in the lower right corner to scale the chart window or manually determine the dimension of the chart by entering values in the boxes below the chart ("Chart Size"). We recommend doing this step first, but you can change the size of your chart at any point.


In the "Refine" tab, we see five panels. The first panel lets you customize the range start and the range end by selecting one of the numeric columns. In the case of our chart, we want to show the pay gap between Women and Men so we set the range start to "Women" (women's average earnings) and the range end to "Men" (men's average earnings). It can also be the difference between dates, percentage points, etc. 

Hint: It doesn't really matter which one of your numeric columns you choose for the Range start and which one you choose for the Range end. The chart won't look different. However, you will need to remember which column you chose for which to select your colors a bit later.

For our chart, the panel looks like this: 


The second panel lets us customize the labels. Here we can choose how you want your labels to look. Do you want your labels to be left or right-aligned? Do you want to show values next to the range plots? The absolute difference or the % change? You can try these different settings out for yourself and see what happens. 

The most interesting setting here is the  Number format. Here we can decide how our values are shown (if we chose to display them). Here are three examples:

  • 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 our chart, the panel looks like this at the end: 

Horizontal axis 

In the third panel in the "Refine" tab, we can customize how our x-axis should look like:

  • Axis range: We have three options: roundexact, and custom. Datawrapper chooses the extent of your x-axis based on the minimum and maximum value of your whole data. Selecting exact will accommodate the chart precisely to its width while round will show the next gridline outside of the exact width. Custom lets you decide the exact range of the x-axis by allowing you to manually enter the numbers. 
  • Number format: Our values might be percentages and we want to add a percentage  sign; or  our values are very high numbers (e.g. 3844929) and we want to shorten them (e.g. to 3.8m). With this option, we can make our data more readable. 
  • Custom grid lines: Your charts will have grid lines by default – but if you want to change this, you can do that here. Type in the numbers on which you want to see grid lines. E.g., typing in the two numbers "0, 20" will result in two grid lines on the entire x-axis: One at zero, the other one at 20. 
  • Tick position: Here, you can decide whether you want the ticks at the top or the bottom of the chart. 

For our chart, the panel looks like this at the end: 


In the fourth panel in the tab "Refine", we can choose colors for our dots on both sides: The range start color and the range end color. Click on the color to choose an individual color and customize the appearance of the range: 

Sorting & Grouping

In this fifth and last panel, we have three important decisions to make:

  • Sort rows: How should the lines and labels be sorted? You can keep the order of your spreadsheet, or you can sort the lines by the values of the range start (the column "Women", in our case), by end date ("Men"), by the difference between the start and end date or by the percentage point change between the start and the end date. 
  • Reverse order: If you select this option, your chart will be in reverse order of the default order defined in the spreadsheet. 
  • Group bars by column: You can upload an extra column to put categories into groups. In our case, we could have a column that indicates if our education levels are below high school or above the high school level. Each row in this column would have either the text "below high school" or "above high school". If we chose this column as our "Groups", the chart would make a separation between these two levels.

For our chart, the panel looks like this at the end: 



In the Annotate tab, you're first asked to give your visualization a title, description, notes, source, byline, and an alternative description for screen readers. You can find a detailed explanation of all these Annotate options here.

Highlight element

In the 2nd panel in the "Annotate" tab, we can emphasize the dots from a certain column. If you want to emphasize certain labels (categories) instead, just go directly into the label in the chart, select the label of your choice and make it bold with pressing Strg+B (Windows) or Cmd+B (Mac). 



In the Layout tab, you can select an output locale, change the design theme and footer options, and enable social sharing. Find a detailed explanation of all the Layout options here.



After we have worked through the four tabs of step 3: Visualize, we can now proceed to step 4: Publish & Embed

The best way to use a Datawrapper chart is by embedding it directly on your website. To do that, click the big blue button that says " Publish chart". Then, copy & paste the embed code snippet into your website or CMS. You can also download your chart as a PNG or PDF. All Datawrapper users- regardless of their subscription plan- have the option to download their charts as PNG. Users of Custom and Enterprise plans also have the option to download their charts and maps as PDF for printing or modifying them later in Adobe Illustrator. Click here for more information on the different pricing plans of Datawrapper.