Customizing your arrow plot

After importing the data for your arrow plot, you can refine, annotate and design your arrow 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.

Arrows

In the "Refine" tab, we see five panels. The first panel lets you customize the arrow start and the arrow end by selecting one of the numeric columns. 

  • Arrow start: Select the column header that contains the value of your earlier time point. In our case, we choose the column "2009". 
  • Arrow end: Select the column header that contains the value of your later time point. In our case, we choose the column "2013". 

Hint: It doesn't really matter which one of your numeric columns you choose for the Arrow start and which one you choose for the Arrow 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: 

Labels 

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 arrows? 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: 

Appearance

In the fourth panel in the tab "Refine", we can choose colors for our arrows. We can choose one color for all our arrows (click on "Base color" to change the default color). When we click on "Customize colors", we can choose individual colors for each arrow. In our chart, we do that to give each arrow the color of the party it represents:

In this panel, we can also decide if our chart should have a color key or not. If we click on the text field next to a color, we can also change the description. Our colors are intuitive for our German audience, so we decide against a color key altogether.

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 start date (2009, in our case), by end date (2013), 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: 


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 using the title to tell your readers the most interesting aspect 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 mention 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 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). 


3

Design

In the ''Design'' tab under step 3: Visualize, you can select a  preset layout. Should it come with the Datawrapper layout or in the custom design of your organization? 

You can also change the Output Locale for your map. This affects the language of the attribution in the bottom left of your map and defines decimal and thousand separators as well as translation of month and weekday names.

You can also and enable social sharing function to share your work. If you select the checkbox, the share buttons for Facebook, LinkedIn and Twitter will appear on the top-right corner of your map. Users of the Free plan have two options: one layout with and one without the "Get the data" link. Users of Datawrapper's Custom and Enterprise plan have the option 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. 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. The PNG option is something that is available to all Datawrapper users regardless of their subscription plan while the PDF option is available only to users of the Custom and Enterprise plan. Click here for more information about the pricing plans that Datawrapper offers.