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I'm working on an edtech product where some of our traffic lands on webpages about textbooks.

Textbooks belong to subjects like Algebra, Calculus and Spanish. In each of our subjects, we have "whales" - individual books that account for a large percent (~20%) of total subject traffic.

Year over year, these whales grow or shrink (sometimes books are replaced in a school, or schools drop textbooks altogether). This change in whale traffic contributes to a big change in overall subject traffic.

I'm trying to figure out how to visualize this change, given a dataset that looks something like the table attached below (it shows only 2 months traffic per book, but I have access to all the months).

I've tried overlapping histograms (and boxplots), where each histogram is a month. But this visualization doesn't indicate how huge my whales (outliers) are, and how much influence they have.

Any help on chart types or how to otherwise tell this story would be much appreciated.

enter image description here

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2 Answers 2

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To visualize change in the size of multiple entities that are contributing to a total through time, e.g. total (t) = book_1 (t) + book_2 (t) + ..., we can use Stacked Area Plot. This plot can be used for normalized and un-normalized (absolute) values.

Preprocessing

  1. For large number of entities, to avoid cognitive load, we can keep only those entities that become significant (whale) at some point in the plot, and group all the others under an "ordinary" entity. This way, cognitive load is minimized and only those entities that matter at some point are distinguished. For example, distinguishing books that have more than 10% of traffic at some point in the plotted time span.

  2. If total fluctuation is very high, logarithm of values can be plugged into the plot.

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  • $\begingroup$ This is helpful. But these charts get very noisy with hundreds of observations per period. (We have hundreds of books per subject.) And it takes a lot of cognitive load, at a glance, to tell what's growing and what's shrinking. I do appreciate the suggestion! $\endgroup$
    – samthebrand
    Commented Mar 19, 2019 at 20:35
  • $\begingroup$ @samthebrand I updated the answer for this problem $\endgroup$
    – Esmailian
    Commented Mar 19, 2019 at 21:03
  • $\begingroup$ Thanks @esmailian. This is a good answer, but I don't think it is THE answer, given that I'm interested in visualizing YOY change. For a stacked area chart I would have to look at latest period and then compare its relative size to the period twelve months prior. This feels hard. There's got to be a better way. $\endgroup$
    – samthebrand
    Commented Mar 19, 2019 at 21:31
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You could try to plot data for each book as a trajectory ($X$ coordinate is the month and $Y$ is uniques counter). Something like this

This approach works if you have thousands of books. The whales will be spikes in this plot.

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