Show y_ticklabels in nautical pair with common axes
I am using a pair-sided pair to plot multiple independent variables relative to the dependent variable.
import seaborn as sns
iris = sns.load_dataset("iris")
x_vars = ['sepal_length', 'sepal_width', 'petal_length']
y_vars = ['petal_width']
pp = sns.pairplot(data=iris, x_vars=x_vars, y_vars=y_vars)
Now I want to add y-axes and y-labels to the second and third subplots.
Adding Y-axis labels is easy:
pp.set(ylabel='petal_width')
But I can't for the life of me figure out how to show y_ticklabels.
Things like:
pp.set(yticklabels=np.arange(-0.5, 3.01, 0.5))
or
for i in range(3):
ax = pp.axes[0,i]
ax.set_yticks(np.arange(-0.5, 3.01, 0.5))
ax.set_yticklabels(np.arange(-0.5, 3.01, 0.5))
ax.set_visible(True)
irrelevant.
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Just turn yticklabels
back to visible and you're good to go at the desired subheading:
import seaborn as sns
iris = sns.load_dataset("iris")
x_vars = ['sepal_length', 'sepal_width', 'petal_length']
y_vars = ['petal_width']
pp = sns.pairplot(data=iris, x_vars=x_vars, y_vars=y_vars)
_ = plt.setp(pp.axes[0,1].get_yticklabels(), visible=True) #changing the 2nd plot
_ = ...
here is to suppress unwanted printing in interactive environments.
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3.0.3 is my version of matplotlib and CT Zhu's answer didn't work for me and I don't know why.
I found the answer here .
You can use the method tick_params
on your desired subplot to show yticklabels
by passing a parameter labelleft=True
. (there are 2 ways)
"""enabling yticklabels for all subplots"""
import seaborn as sns
iris = sns.load_dataset("iris")
x_vars = ['sepal_length', 'sepal_width', 'petal_length']
y_vars = ['petal_width']
pp = sns.pairplot(data=iris, x_vars=x_vars, y_vars=y_vars)
# iterating over all subplots
for ax in pp.axes.flat:
# labelleft refers to yticklabels on the left side of each subplot
ax.tick_params(axis='y', labelleft=True) # method 1
# ax.yaxis.set_tick_params(labelleft=True) # method 2
plt.show()
From the docs tick_params
.
Change the appearance of ticks, tick marks and grid lines.
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