import pandas as pd
from plotnine import ggplot, aes, after_scale, geom_bar, theme_classic
after_scale
The bars in geom_bar
have two aesthetics that control the coloring; fill
for the interior and color
for the boundary/edge. Using after_scale
we can create a matching combination of these two.
Start off with a mapping to the color
.
= pd.DataFrame({"var1": [1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5]})
df
("var1", color="factor(var1)"))
ggplot(df, aes(+ geom_bar(size=1)
)
We can match the color
with the fill
.
("var1", color="factor(var1)"))
ggplot(df, aes(+ geom_bar(aes(fill=after_scale("color")), size=1)
)
As after_scale
takes an expression, for the fill
aesthetic we can modify the color
by adding to it an alpha channel i.e. '#AABBCC'
to '#AABBCC66'
.
("var1", color="factor(var1)"))
ggplot(df, aes(+ geom_bar(aes(fill=after_scale('color + "66"')), size=1)
)
We rely on the fact that you can append a string to all elements of a pandas series
pd.Series(['#AABBCC', '#112233']) + '66' == pd.Series(['#AABBCC66', '#11223366'])
With a fitting theme.
("var1", color="factor(var1)"))
ggplot(df, aes(+ geom_bar(aes(fill=after_scale('color + "66"')), size=1)
+ theme_classic()
)