Continue with the steps Refine, Annotate, and Design to finish customizing your chart. We'll cover this in a separate short tutorial which you can read here. Once you're in the "Visualize" tab, choose "Scatter Plot" from the grid of available chart types and Datawrapper will create the first iteration of your data. " is ticked so that Datawrapper correctly assigns the values to the labels.Ĭlick on "Proceed" and Datawrapper will take you to the next step. A Scatter Plot permits visual analysis of pole distribution by plotting symbols representing the number of approximately coincident poles at a given orientation. (As you can see, we uploaded two more columns, to assign colors to each dot and to define their size.) Make sure that the box "First row as This is what the dataset looks like once it is uploaded into Datawrapper. Looks like the table above, you can copy it into Datawrapper and click "Upload and continue". That's how the first five rows of our data look like for the chart you can see above: Country The values do not have to be of the same measure (in our examples, the GDP is in US-Dollars and the life expectancy is in years). You can have more (numeric) columns, but you'll need at least two. These values will define the positions of the dots in the chart. The following two column s containing numeric values that will be used as x- and y-coordinates.The first column defining labels of the dots.Your dataset should be formatted as follows. For example, here is the dataset that powers the chart above. You can copy
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