How to scale Seaborn's y-axis with a bar plot

Question

I'm using factorplot(kind="bar").

How do I scale the y-axis, for example with log-scale?

I tried tinkering with the plots' axes, but that always messed up the bar plot in one way or another, so please try your solution first to make sure it really works.

Answer 1

Considering your question mentions barplot I thought I would add in a solution for that type of plot also as it differs from the factorplot in @Jules solution.

import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="whitegrid")

xs = ["First", "First", "Second", "Second", "Third", "Third"]
hue = ["Female", "Male"] * 3
ys = [1988, 301, 860, 77, 13, 1]

g = sns.barplot(x=xs, y=ys, hue=hue)
g.set_yscale("log")
_ = g.set(xlabel="Class", ylabel="Survived")

And if you want to label the y-axis with non-logarithmic labels you can do the following.

import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="whitegrid")

xs = ["First", "First", "Second", "Second", "Third", "Third"]
hue = ["Female", "Male"] * 3
ys = [1988, 301, 860, 77, 13, 1]

g = sns.barplot(x=xs, y=ys, hue=hue)
g.set_yscale("log")

# the non-logarithmic labels you want
ticks = [1, 10, 100, 1000]
g.set_yticks(ticks)
g.set_yticklabels(ticks)

_ = g.set(xlabel="Class", ylabel="Survived")

Answer 2

Note that seaborn.factorplot was renamed to seaborn.catplot

import seaborn as sns
import matplotlib.pyplot as plt
    
titanic = sns.load_dataset("titanic")

g = sns.catplot(x="class", y="survived", hue="sex",
                   data=titanic, kind="bar",
                   height=5, palette="muted", legend=False, log=True)
plt.show()

You can use Matplotlib commands after calling factorplot. For example:

g = sns.factorplot(x="class", y="survived", hue="sex",
                   data=titanic, kind="bar",
                   height=5, palette="muted", legend=False)
g.fig.get_axes()[0].set_yscale('log')
plt.show()

Answer 3

If you are facing the problem of vanishing bars upon setting log-scale using the previous solutions, try adding log=True to the seaborn function call instead. (I'm lacking reputation to comment on the other answers).

Using sns.factorplot:

import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")

titanic = sns.load_dataset("titanic")

g = sns.factorplot(x="class", y="survived", hue="sex", kind='bar',
                   data=titanic, palette="muted", log=True)
g.ax.set_ylim(0.05, 1)

Using sns.barplot:

import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")

titanic = sns.load_dataset("titanic")

g = sns.barplot(x="class", y="survived", hue="sex",
                data=titanic, palette="muted", log=True)
g.set_ylim(0.05, 1)