I have a simple factorplot
import seaborn as sns g = sns.factorplot("name", "miss_ratio", "policy", dodge=.2, linestyles=["none", "none", "none", "none"], data=df[df["level"] == 2]) 
The problem is that the x labels all run together, making them unreadable. How do you rotate the text so that the labels are readable?
I had a problem with the answer by @mwaskorn, namely that
g.set_xticklabels(rotation=30) fails, because this also requires the labels. A bit easier than the answer by @Aman is to just add
plt.xticks(rotation=30) 
g.set_xticklabels(g.get_xticklabels(), rotation=30). Assign it to a variable if you want to suppress the output.
plt.xtics worked for me.
plt.tight_layout(), so that the margins are adjusted to fit the textg.set_xticklabels(rotation=30) works on FacetGrid nowYou can rotate tick labels with the tick_params method on matplotlib Axes objects. To provide a specific example:
ax.tick_params(axis='x', rotation=90) 
This is still a matplotlib object. Try this:
# <your code here> locs, labels = plt.xticks() plt.setp(labels, rotation=45) Any seaborn plots suported by facetgrid won't work with (e.g. catplot)
g.set_xticklabels(rotation=30) however barplot, countplot, etc. will work as they are not supported by facetgrid. Below will work for them.
g.set_xticklabels(g.get_xticklabels(), rotation=30) Also, in case you have 2 graphs overlayed on top of each other, try set_xticklabels on graph which supports it.
You can also use plt.setp as follows:
import matplotlib.pyplot as plt import seaborn as sns plot=sns.barplot(data=df, x=" ", y=" ") plt.setp(plot.get_xticklabels(), rotation=90) to rotate the labels 90 degrees.
If anyone wonders how to this for clustermap CorrGrids (part of a given seaborn example):
import seaborn as sns import matplotlib.pyplot as plt sns.set(context="paper", font="monospace") # Load the datset of correlations between cortical brain networks df = sns.load_dataset("brain_networks", header=[0, 1, 2], index_col=0) corrmat = df.corr() # Set up the matplotlib figure f, ax = plt.subplots(figsize=(12, 9)) # Draw the heatmap using seaborn g=sns.clustermap(corrmat, vmax=.8, square=True) rotation = 90 for i, ax in enumerate(g.fig.axes): ## getting all axes of the fig object ax.set_xticklabels(ax.get_xticklabels(), rotation = rotation) g.fig.show() For a seaborn.heatmap, you can rotate these using (based on @Aman's answer)
pandas_frame = pd.DataFrame(data, index=names, columns=names) heatmap = seaborn.heatmap(pandas_frame) loc, labels = plt.xticks() heatmap.set_xticklabels(labels, rotation=45) heatmap.set_yticklabels(labels[::-1], rotation=45) # reversed order for y If the labels have long names it may be hard to get it right. A solution that worked well for me using catplot was:
import matplotlib.pyplot as plt fig = plt.gcf() fig.autofmt_xdate() 
Use ax.tick_params(labelrotation=45). You can apply this to the axes figure from the plot without having to provide labels. This is an alternative to using the FacetGrid if that's not the path you want to take.
seaborn.objectswith v0.12, see How to rotate the xticks with seaborn.objects