
Visualization techniques for different data sets - rocker_pj
https://mlwhiz.com/blog/2019/04/19/awesome_seaborn_visuals/
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Theodores
What surprises me with visualisation is that you soon find yourself on your
own when it comes to making a 'simple' graph. This takes you out in to a whole
world of coding that nobody else will ever re-use.

The examples out there will not do for _your_ data and even if you wonder 'am
I using the wrong chart for this?' you can find that you are not.

Recently I needed to do a stacked bar chart with different things in each
stack. Imagine column 1 - fruit - with that broken down by
apples/bananas/oranges and column 2 - vegetables - with that broken down by
tomatoes/potatoes/carrots.

The other problem area was colouring the chart. I generated colours in the hsl
colour space so that where something was on the chart determined colour and
how much of it there was determined saturation/lightness. Some people get
offended by eXcel style hard colours so I could not just use random clashing
colours and call it a day.

Beautiful visualisations are hard, even with the best graph tools out there I
expect some inevitable situation of being an edge case and having to find
solutions the hard way. The goal being so that nobody even notices the hard
work put in. Only if the graph is ultra intuitive and simple is it going to
work with some audiences. Simplicity is hard.

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rocker_pj
Experimentation when it comes to visualization is a pretty inherent task.
Whenever, and I mean literally every time, I start creating a graph, I end up
opening at least 5-7 SO tabs, matplotlib, and seaborn docs, etc.

It is just that visualizations are not a solved thing yet.

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alexilliamson
I'm finding this to be pretty accurate for python viz, but I gotta say, when I
was working in R, I got to the point where I could make most graphs without
looking at the docs.

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xtiansimon
Nice article. Concise. Code examples. The plots look good. I like the way the
author takes several passes on each problem--'do better' as the author says.

Even when focused carefully on the coding and choosing the right plot for the
data, an article about plotting is still so much about the data. And so, it's
ultimately disappointing if you can't relate the data to your most common
problems.

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the8472
Box+swarm plots are ok if you only have a few data points. if you have more
there are better visualization options that don't obscure the PDF.

[https://wellcomeopenresearch.org/articles/4-63/v1](https://wellcomeopenresearch.org/articles/4-63/v1)

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lichtenberger
This is very nice. It reminds me, that I'd love to spend some time on novel
visual analytics tasks again (as it was one of the main topics while studying)
:-)

For instance in the context of Text Mining or geo-spacial stuff.

Thanks for the submission and happy easter :-)

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rocker_pj
Thank you lichtenberger. Keep learning and happy easter

