If I can figure out how to give each plot-pict a name, I'll be able to use pin-over and rt-find to annotate questions. For now only the title text is named. With the title pict named inset let me place the response table without relying on coordinates discovered from a bitmap in GIMP.
The code and data are below.
This code was broken for a while, the .png-generation portion is still too repetitive. The code takes questionnaire results and provides a faceted (R ggplot2-like) view with an .html page that list questions with a visualization of their results for the individual, the individual's department(faculty), and the department's(faculty's) university.
Experience with Racket's path utilities over the past weeks (and today's discovery that regexp-replace works with paths!) helped to clean up the part that filters plot images.
Other work demands attention and time, but it's awful to leave code in a broken state.
While rushing to finish pasting .png files into a word processor document, I noticed that plots need a title for context. Maybe if I was able to completely avoid office software and stay with generated html pages it wouldn't matter as much, but while pasting images into documents it was hard to see which semester the plots belonged too.
The generated html page was ok when printed from firefox with the Landscape setting but the “float” layout broke with my laptop screen. Looking over css grid again helped with that issue. Printing to .pdf from Firefox is helpful but the files got really big for my recent pages with plot images..
The code needs editing, but I like this view of questionnaire data where “factor” responses of 1 and 2 are negative, 3 is seemingly neutral, and 4 and 5 are positive. It seems possible to see things with this view that might not be possible with an average/mean of the responses.
The visualization needs to be on a page with the full text for the questions, the symbols for the numbered responses, the tables for the data, and an attempt to explain the visualization.
While using questionnaire data to learn plotting, questions come to mind. Averages don't make sense for “ranked” “factors”, for numbered responses to questions about how much a person agrees or disagrees with a question. Maybe seeing the percentage and number of positive responses versus negative responses will help in the search for meaning in the data.
With Racket it is possible to transform and view the data however you like. It's nice to be able to implement a view out of curiosity. I'm hoping the stacked lines with their labels provide enough hints for people to figure out that they are combinations of responses of 4 and 5 in a positive direction, and 1 and 2 in a negative direction.
If there is time to go over the code again there must be less repetitive way to stack negative lines after stacking positive lines. Getting started on that gave me a change to use Racket's define to give the pnt-w-lbl procedure an optional argument.
Years ago with gnuplot I plotted “enthused”熱意 results against “satisified”満足 responses. Naomi Klein quoted a Harpers article by a professor that said he refused to be “cool” like a Marshall McLuhan screen.
For now though, I just want to see how Racket can replace two pages oddly scaled visualizations and averages. It's time to move into other work, after adjusting the css styles so that the generated page fits onto two A4 papers.
Here's proof that the code pasted in below worked in DrRacket:
Developing faculties for designing programs and visualization with Faculty Development Questionnaires. In the spirit of “Nothing about us without us”, ideally, students would design the questionnaires. We would view the data with Racket's help, and get started thinking about what sort of classes, what sort of universities, we need.
It was good to get that feeling that capacities/abilities/powers were growing while doing this. Racket's documentation, DrRacket, and Emacs are great for self-directed exploratory learning. With enough time to become the equivalent of a “native speaker” in Racket, developing a Graded Direct Method for learning the language could be one way of developing “effectively capable people”(I.A. Richards).
This sort of visualization may let me replace bar charts. The panel or facet approach to interleaved discrete histograms might be good for on-screen browsing, but this sort of plot might be easier on the printer and ink supply.
Discussion in Diaspora* post comments provides motivation to explore more code and presentation. (fn:1~
Now I have to see about getting these separate images aligned into one eye-span for analytical viewing.
I was feeling overwhelmed while try to label the bars in interleaved, discrete histogram plots of percentages. So I went back to the basics: lines and points. There is probably a straightforward way to montage a series of plots together, but I haven't found it yet. Maybe series of this sort of plot panel for different results can be helpful if grouped and aligned on an .html page and seen in a browser.
DrRacket is great for checking code developed with Emacs geiser-mode. After pasting the text from and Emacs buffer and clicking the “Run” button, DrRacket reminds me of all the definitions from previous scripts and REPL experiments that never made it into the file.
This code is still clumsy, the process isn't clear enough in my mind for elegant solutions. But working through the process is great for learning. This may be a way to re-discover the faceting that R/ggplot2 makes possible. I think this is the best way to get a feel for how an individual teachers results are situated in relation to the groups: the individual's department and school.
Racket plot and scribble/html with stacked-histograms and output-xml are working well. It was fun to play with plot keywords and think about printing the data visualizations, but for quick comparisons in the browser the defaults seem better.
I imagine DrRacket will make the code below work with a Windows computer too. How would Windows users be able to find their home directory, Racket's (current-directory) and get their bowser to show “/FD201801/FD-Anketo-Results.html”... The file-separator slashes are probably different too. But that sort of detail can be overcome when a Windows user shows an interest in testing the code and visualization...
It was good training to work with associative lists, to use two a-lists to generate a new a-list. Using a-lists allows for the generation of useful titles and file names that match the data used for the visualization.