Customizing your dot plot

After importing the data for your dot plot, you can refine, annotate and design your dot plot in step 3: Visualize. Let's walk through the main steps Refine, Annotate and Design before publishing the 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 ("Resize to"). We recommend doing this step first, but you can change the size of your chart at any point.

Customizing the axes

In the "Refine" tab, we see three panels. The first panel lets us customize our axes. Here we can choose which element in your chart shows which data:

  • Labels: Select the column header that contains labels for each row. These labels are in your category-column. We'll choose the column "Country" for our labels.
  • Groups: You can upload an extra column to put categories into extra groups. In our case, we could have a column that indicates the continents our countries are in. Each row in this column would have the name of the continent in it: "Europe", "Australia", "Asia", etc. If we chose that column as our "Groups", the chart would group all the countries that are on the same continent together. 

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


In the 2nd panel in the "Annotate" tab, we can make three kinds of decisions about labels:

  1. Bar label alignment: Should the labels (the names of your categories left of the actual lines) be left-aligned or right-aligned? Left-aligned is the default, but depending on the labels, right-aligned could be more readable.
  2. 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. 
  3. Custom grid lines: Your charts will have grid lines without touching that option – but if you want to change the default, 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. 

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


In the third and last panel in the tab "Refine", we can  choose colors for our dots. We can choose one color for all our dots (click on "Base color" to change the default color). When we click on "customize colors...", we can choose individual colors for all that dots that represent values from one column. In our chart, we do that to give the dots that represent the values from our columns "Total", "Male" and "Female" different colors:

In this panel, we can also decide if our chart should have a color key or not. And we can decide if our chart should display a thick line between our dots with "Highlight range between dots"

Below the three panels, you can find a fourth option: To extend the range of the x-axis. Datawrapper chooses the extent of your x-axis based on the minimum and maximum value of your whole data. If you like to change the default extent, you can do that here. Opposite to bar charts, you can have a minimum value that's greater than zero.



Describe chart

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 what's interesting about this chart – the one key statement that you want to show on 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 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 themselves. Both, source name and source URL, should be filled out on every map or chart to increase transparency. E.g. US Bureau of Labour Statistics, August 2017

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 this last step, we can select a preset layout, output locale and enable social sharing functions 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 Custom and Enterprise plan have the freedom to choose either between the default theme or their own custom theme



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 in two formats. First, users of all subscription plans have the option to download their chart as a PNG. Custom and enterprise plan user also have the option to download their chart as PDF. Click here for more information on the different pricing plans of Datawrapper.

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