
A Better Default Colormap for Matplotlib - martian
http://bids.github.io/colormap/
======
stared
When it comes to plot colors in matplotlib, it's why I start with

import seaborn as sns

to get a nice plot theme, not "good old 90s" style. See:
[https://speakerdeck.com/pmigdal/teaching-machine-
learning?sl...](https://speakerdeck.com/pmigdal/teaching-machine-
learning?slide=5)

~~~
serialx
This, changes everything.

The theme seaborn uses is actually a direct clone from ggplot2 from R

~~~
stared
Yes. Though, I think that 'whitegrid' is a cleaner theme (if there were axes).

For ggplot theme, in matplotlib there is

plt.style.use('ggplot')

(see also: [http://pandas.pydata.org/pandas-
docs/stable/visualization.ht...](http://pandas.pydata.org/pandas-
docs/stable/visualization.html)).

~~~
gammarator
'ticks' plus sns.despine() is my favorite.

------
jks
This will be the default in Matplotlib 2.0, and a beta was just tagged:
[http://article.gmane.org/gmane.comp.python.matplotlib.announ...](http://article.gmane.org/gmane.comp.python.matplotlib.announce/9)

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jules
In the talk when he showed the 3 similar maps getting equal score, and then
the green one getting a much higher score, that could easily be because people
couldn't decide between the 3 similar maps, to they went with the one
different map. To do a proper comparison the test should be 1-1 or 3-3, not
3-1.

~~~
xiphias
They wanted green because it's a python library. He goes into the details in
the talk

------
martian
OP here: really worth watching the embedded video on this topic. Viridis is
born out of an awesome, intense deep-dive into research on human vision and
perception.

------
franblas
I'm mostly using seaborn
([https://web.stanford.edu/~mwaskom/software/seaborn/](https://web.stanford.edu/~mwaskom/software/seaborn/))
to wrap matplotlib graphs but great to see a direct alternative into the
matplotlib library.

------
xioxox
If you're interested in colour maps, cubehelix [1] is a useful scheme to make
intensity maps which display well when converted to greyscale.

[1]
[https://www.mrao.cam.ac.uk/~dag/CUBEHELIX/](https://www.mrao.cam.ac.uk/~dag/CUBEHELIX/)

------
mbostock
I ported these color scales to d3-scale and D3 4.0:

[https://github.com/d3/d3-scale/blob/master/README.md#sequent...](https://github.com/d3/d3-scale/blob/master/README.md#sequential-
scales)

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yoodenvranx
I started using viridis a few weeks ago and I love it!

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Aardwolf
Is it strange that I find the old "JET" the best? It uses the most hues
(green, yellow, red and blue are all there), so things are the most
distinguishable. The others are either only blue/green/yellow, or only
purple/red/yellow.

~~~
Scaevolus
Quick, which represents a larger value, green or red?

Having a gradient between two colors, from dark to light, makes it easier to
determine the scale. Rainbow gradients look nice, but hue transitions are
nowhere near as intuitive as luminance.

~~~
pdabbadabba
I think you're both correct, but your points respond to different needs. For
some types of results (and audiences and modes of presentation) its more
important that the reader be able to determine the approximate value that a
color corresponds to than that the reader be able to quickly intuit the
progression of values. For me, Jet is better at the former while Viridis et al
are better at the latter.

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slmouradian
I dislike that the whole page, including the updates, do not contain any
dates...

~~~
carreau
Good point. I'll ping authors to update page with dates.

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tixzdk
Javascript version: [https://github.com/politiken-journalism/scale-color-
perceptu...](https://github.com/politiken-journalism/scale-color-perceptual)

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jxy
If you use gnuplot, which I do exclusively, you may like this repository:

    
    
        https://github.com/Gnuplotting/gnuplot-palettes

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wnkrshm
I'm pleased. They look extremely similar to the gnuplot and gnuplot2 color
maps already present in matplotlib, my favorites.

------
donquichotte
I also enjoy using Olga Botvinnik's prettyplotlib:
github.com/olgabot/prettyplotlib

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Bromskloss
That was an amusing talk. I had fun watching it.

