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. In this tutorial, we'll walk you through all these steps to create the following chart:

1

Refine

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 to do 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: 

Labeling

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. Numer 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 gridlines. E.g., typing in the two numbers "0, 20" will result in two gridlines on the entire x-axis: One at zero, the other one at 20. 

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

Appearance

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.

These are all the options you can find in the Refine tab. Let's move on to the Annotate tab. Here you'll find two options: "Describe chart" and "Highlight element".


2

Annotate

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 writing   in the title what's interesting about the map – the one key statement that you want to show on this map if you have one. 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 specify 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 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). 

Afer explaining the Annotate options, there's only one tab left: Design. 


4

Design

In this last step, we can select a preset layout and enable social sharing functions to spread your work. 

  • Users of the free plan or Single users have two options: One layout with and one without the "Get the data" link
  • Users of Datawrapper Team are able to select a custom layout here 

4

Publish

After we worked through the four tabs of step 3: Visualize, we can now proceed to step 4: Publish & Embed. Here we can select a preset layout and enable social sharing functions to spread your work. Click on "Publish" and you'll be directed to the "Publish & Embed" page.

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 " Embed chart on website". Then, copy & paste the embed code snippet into your website or CMS. You can also download your chart as a PNG or PDF by upgrading to a paid Single or Team account. Click here for more information on the different pricing plans of Datawrapper.

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