I thought the lines between the inner and outer circles would probably be the next most difficult thing to tackle, but to properly do that I first needed my inner circle. What about adding a thick stroke? And yup, that fixed it enough for me, haha (*^▽^*)ゞ What to do about those crisp outer edges?. So I converted a simple version into a block to perhaps use for another time and took a closer look at the original SVG version again. Well, that's how (dataviz) design sometimes works, hours of work on something that never makes it to the end. It was sometimes a bit hard to actually get a feeling for the true color of circle because it contained only a few CMYK dots in itself (ー_ー﹡ ) as expected the circles were so small that there wasn't "enough CMYK" going on. These two circles would then be connected by lines to show which characters appeared in which chapters.Īnd then I applied it to all the circles from the 50 chapters and. So that's why I went with the layered approach of a small circle for all characters and around that another circle with all chapter color clusters. However, with 50 chapters, I really needed as much space as I could get. Although at first I wanted to do a semi circle, with the color clusters to the right and character info the the left. Placing the color clusters in a radial layout was also an obvious choice after that. Having a cluster of small colored circles per chapter seemed like a logical/interesting step.
#Read card captor sakura how to#
I started with how to visualize the colors. A more concrete idea for one aspect led to a vague idea for the next part of the data which I then explored. Sketchįiguring out the design for this project came slowly. I find that the easiest and as a bonus, it doesn't clutter my JavaScript code. I prefer to prepare all data beforehand in R. Well, nothing else to do but to read all chapters again myself while slowly filling an Excel file with the info I needed ¯\_(ツ)_/¯ĭue to the "layered" visual result of this project, I eventually sliced and diced all of this information (who is in each chapter/cover image, totals per character/chapter, relations between characters, color distributions, and more) into about 7 separate small files throughout the creation process. But sadly, only the first 8 chapters contain information. The CCS Wiki page on each chapter seemed like just the resource I needed. To complement this data about the chapter covers, I also wanted to gather information about which characters appeared in each chapter and which "card" was captured in which chapter (CCS is about Sakura collecting so-called magical Clow cards). I therefore searched for and downloaded the corresponding color image from the CCS Wiki page. However, all of those chapter covers have since been published in full-color in several CCS art books. In my volumes the covers are printed in black and white. I went through all 12 CCS volumes to see what image was on the cover of each chapter. There are 50 chapters in the original CCS manga, divided into two "arcs". I therefore thought that creating a visualization that would abstract the colors of each cover into 3 - 8 colors would be fun and new for me. And I've never before done any kind of analysis based on image data. I therefore wanted to investigate the covers through data somehow. Especially the covers from each chapter, which are tiny works of art (the image above is the cover for chapter 23). One of my favorite things about CCS is how beautiful the writers, CLAMP, make each page. Therefore, while thinking of what to do for our Fearless topic, I just couldn't shake the feeling of wanting to do something with Cardcaptor Sakura (CCS), a brave, fearless, and kind magical girl. Nevertheless, after 20 years a new "arc" of Cardcaptor Sakura has started again recently. I almost chose this subject for our Nostalgia topic, but eventually went with Dragonball Z then. I'm still dreadfully jealous of how perfect and cute practically each panel of the manga looks. I even had to travel all the way to the biggest city of our province to buy a new volume. It was the first manga I owned, when manga was practically unknown in the Netherlands (still is actually (╥﹏╥) ).
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