Automatic placement of region labels is a di cult problem that we haven’t had time to solve yet. As an interim measure, you can see the name and data associated with each region in a tooltip (i.e. a small information window) when you click on the region.
Below each map or cartogram displayed on this website there is a download button. By clicking it, you can download an SVG image containing the map. SVG files contain vector images, and can be edited and converted by Adobe Illustrator or Inkscape, a free, open source alternative. If you would simply like to convert your SVG map to a PNG image to use in a document or paper and don’t have access to these programs, you can use this website.
It usually takes just a few seconds to generate a cartogram using this website. A progress bar will give you an indication of how far the calculation has already proceeded. If you can’t see a cartogram at the end, please read our answer to “what went wrong?”
This website uses the Fast Flow-based method developed by Michael T. Gastner, Vivien Seguy, and Pratyush More. You can learn more about how this method works by reading the paper they published in the journal PNAS. If you publish an image produced by go-cart.io, please include a reference to the PNAS paper.
If the algorithm can’t finish within one minute, we’ll show you the data as a bar chart instead of a cartogram. The bar chart may reveal the cause of the problem. Have you tried to make a small region very large? For example, did you set the objective area of the Vatican City as large as the objective area of Russia? Or did you give a large region an objective area of zero? If yes, the algorithm will struggle with the severe distortions that would be necessary to show the data as a cartogram. In that case, a cartogram may not be the best way to represent your data. Please also see our answer to “What kind of data are suited for generating cartograms?”
The colour of each map region can be changed by editing the values of the ‘Colour’ column in the downloadable CSV template for each map. You should use the hexadecimal colour code format to specify the colours you want. If you are not familiar with this format, you can learn more about it here.
Cartograms are designed to visualize totals, not indices. In general, if it is appropriate to use a pie chart or mosaic plot to visualize a dataset, then it should also be appropriate to use a cartogram. You can refer to the examples of appropriate and inapropriate datasets for use with cartograms below for more guidance:
For some data, the algorithm may not be able to compute a solution. For more information, please see our answer to “What went wrong?”