Plotting tables with DrRacket has been teaching me a lot. It felt wrong to go out of DrRacket and into the shell just to montage (ImageMagick) the row-based and column-based plots together. Racket features plot-pict so it seemed like the right time to start learning the pict library.(fn:1) With picts I was able to vc-append a gray separator between the two plots, and to add pip-arrows-lines to point out connections between the two views.

The plots I work with can become long images. Long picts are awkward to work with in DrRacket. I could only scale to the top, and could not check the lower part of the plot. Enclosing the pict code withpict->bitmap makes iterative development smoother. A bitmap is much easier to scroll in DrRacket.

It took a few attempts to learn how to save the pict->bitmap images to file. I was looking for a basic Scheme-like approach with open-output-file or with-output-to-file but nothing worked. The task of saving plot-pict bitmaps as png files has become my introduction to objects in Racket. You send an object a method and arguments. It didn't make sense to me until reading the ambiguous sentence I just typed. With send you don't send the very next expression somehwere, you send the following expressions to the next expression. So send's second argument (if you see send as a typical Racketfunction) is what gets the rest of the arguments.

The visualizations might be ready to print out and think about.

After putting a table of data into R-style, “long form” lists, Racket's group-by and sort allows for creative labeling and ordering. The hours spent with R/ggplot2 got me ready for “pilfering” ideas into Racket. (fn:2)

Working with this table of fisheries data made it easy to appreciate functional programming with sort. You are free to create a function that will sort, or order, the data. It's simple to adhere to Howard Wainer's rules for “table construction.”(fn:1)

データ表の視覚化で何を気づくかな？「 一本釣漁業」と「囲刺網漁業」はなぜ増えたのかな？ カニも54年に増えたみたい(fn:2)。それは生態系の理由か経済的な理由か？ カニの天敵が減たやろうか、悪影響が出るまで餌が増えたか、 それか、 遠いところから人がカニを水俣に持って来ただろうか？

元の表は原田正純「水俣病」(岩波新書)12ページにあった。

Working with a table full of data worthy of attention is great for keeping focus. Getting data into “long form” as is done with R might not be necessary with Racket, at least not with the simple data I work with for visualizations. The code for this visualization was getting too complex for a few days, I had to go back and get the data into a convenient form. Racket's ->plot-label *number* *digits* makes it easy to arrange for helpful labels.

(“1954” (“mullet” 54453.75 90.75625000000001)