Matplotlib: Rotate x-axis tick labels when don't know x-axis value variable

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I am trying to plot the following dataframe, and then rotate x-axis labels

index   label_h1    label_h2    label_h3    
d1  1.2     2.00    0.0     
d2  5.3     4.00    0.2 
d3  7.00    145.00  4.00

plot code:

plt.figure(figsize=(13,10), dpi= 80)
sns.boxplot(data=df)
plt.yscale("log") 
plt.show()

If I try to rotate labels

fig, ax = plt.subplots(1,1)
ax.set_xticklabels(df.columns,rotation = 90)

I get the error:

UserWarning: FixedFormatter should only be used together with FixedLocator
  ax.set_xticklabels(df_corr.columns,rotation = 90)

How can I rotate the labels when plotting a matrix?

pandas seaborn data-visualization matplotlib python
1 Answers

When you set x ticks labels with df_corr.columns you are using data's columns, which are 4 ('index', 'label_h1', 'label_h2', 'label_h3'), for only three boxes, so you should discard 'index' column:

ax.set_xticklabels([label for label in df.columns if label != 'index'],rotation = 90)

In alternative, as explained by Jody Klymak in the comment below, you can use a easier way with:

ax.tick_params(which='major', labelrotation=90)

Complete code

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv(r'data/data.csv')


fig, ax = plt.subplots(1,1, figsize=(13,10), dpi= 80)

sns.boxplot(data=df, ax = ax)

ax.tick_params(which='major', labelrotation=90)
ax.set_yscale("log") 

plt.show()

enter image description here

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