Rotate axis labels

Question

I have a plot that looks like this (this is the famous Wine dataset):

As you can see, the x-axis labels overlap and thus I need to be rotated.

NB! I am not interested in rotating the x-ticks (as explained here), but the label text, i.e. alcohol, malic_acid, etc.

The logic of creating the plot is the following: I create a grid using axd = fig.subplot_mosaic(...) and then for the bottom plots I set the labels with axd[...].set_xlabel("something"). Would be great if set_xlabel would take a rotation parameter, but unfortunately that is not the case.

Asked By: Eerik Sven Puudist

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Source

Answer 1

Based on the documentation set_xlabel accepts text arguments, of which rotation is one.

The example I used to test this is shown below, though .

import matplotlib.pyplot as plt
import numpy as np

plt.plot()
plt.gca().set_xlabel('Test', rotation='vertical')

Answered By: Jack Haas

Answer 2

While the other answer works, it treats the subplots as if the implicit pyplot interface is being used, while the explicit Axes interface is actually being used. When working with subplots, it is always better to be explicit. Additionally, plt.gca() only gets the last axes.
pandas.DataFrame.plot with subplots=True, and plt.subplots with nrows and / or ncols greater than 1, returns a numpy.ndarray of matplotlib.axes._axes.Axes.
- How to fix ‘numpy.ndarray’ object has no attribute ‘get_figure’ when plotting subplots
- The easiest way to work with the axes array, is to flatten it with .flat, .flatten, or .ravel.
  - What is the difference between flatten and ravel functions in numpy?
  - numpy difference between flat and ravel()
There are several ways to interact with an individual Axes.
1. Iterate through all of them: for ax in axes.flat:
2. Iterate through a slice of them: for ax in axes.flat[-4:]: for the last four.
3. Select a specific Axes to work on after axes = axes.flat: ax[4], ax[-1], etc.
matplotlib.axes.Axes.set_xlabel is used to rotate the axis label.
- Accepts properties from matplotlib.text as **kwargs.
- Also see Rotating the y-axis label
- matplotlib.axes.Axes.set_ylabel can be used to set the various ylabel parameters.

Imports and Sample DataFrame

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

# sinusoidal sample data
sample_length = range(1, 16+1)
rads = np.arange(0, 2*np.pi, 0.01)
data = np.array([np.sin(t*rads) for t in sample_length])

# create a wide dataframe
df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])

# transform df to a long form
dfl = df.melt(ignore_index=False).reset_index()

`pandas.DataFrame.plot` with `subplots=True`

axes = df.plot(subplots=True, layout=(4, 4), figsize=(10, 10), color='tab:purple', legend=False)

# flatten the axes array
axes = axes.flatten()

# iterate through each axes and associated column
for ax, col in zip(axes, df.columns):
    
    # set the axes title
    ax.set_title(col)
    
    # extract the existing xaxis label
    xlabel = ax.get_xlabel()
    
    # set the xaxis label with rotation
    ax.set_xlabel(xlabel, rotation='vertical')

`plt.subplots`

fig, axes = plt.subplots(4, 4, figsize=(10, 10), sharex=True, tight_layout=True)

axes = axes.flat

for ax, col in zip(axes, df.columns):

    df.plot(y=col, ax=ax, title=col, legend=False)
    xlabel = ax.get_xlabel()
    ax.set_xlabel(xlabel, rotation='vertical')

`seaborn.relplot`

relplot is a figure-level function, which returns a FacetGrid, from which the subplots are extracted with axes = g.axes.

g = sns.relplot(data=dfl, kind='line', x='radians', y='value', col='variable', col_wrap=4, height=2.3)

axes = g.axes.ravel()

for ax in axes[-4:]:
    xlabel = ax.get_xlabel()
    ax.set_xlabel(xlabel, rotation='vertical')

DataFrmames

`df.head()`

         freq: 1x  freq: 2x  freq: 3x  freq: 4x  freq: 5x  freq: 6x  freq: 7x  freq: 8x  freq: 9x  freq: 10x  freq: 11x  freq: 12x  freq: 13x  freq: 14x  freq: 15x  freq: 16x
radians                                                                                                                                                                       
0.00     0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   0.000000   0.000000
0.01     0.010000  0.019999  0.029996  0.039989  0.049979  0.059964  0.069943  0.079915  0.089879   0.099833   0.109778   0.119712   0.129634   0.139543   0.149438   0.159318
0.02     0.019999  0.039989  0.059964  0.079915  0.099833  0.119712  0.139543  0.159318  0.179030   0.198669   0.218230   0.237703   0.257081   0.276356   0.295520   0.314567
0.03     0.029996  0.059964  0.089879  0.119712  0.149438  0.179030  0.208460  0.237703  0.266731   0.295520   0.324043   0.352274   0.380188   0.407760   0.434966   0.461779
0.04     0.039989  0.079915  0.119712  0.159318  0.198669  0.237703  0.276356  0.314567  0.352274   0.389418   0.425939   0.461779   0.496880   0.531186   0.564642   0.597195

`dfl.head()`

   radians  variable     value
0     0.00  freq: 1x  0.000000
1     0.01  freq: 1x  0.010000
2     0.02  freq: 1x  0.019999
3     0.03  freq: 1x  0.029996
4     0.04  freq: 1x  0.039989

Answered By: Trenton McKinney

Rotate axis labels

Question:

Answers:

Imports and Sample DataFrame

`pandas.DataFrame.plot` with `subplots=True`

`plt.subplots`

`seaborn.relplot`

DataFrmames

`df.head()`

`dfl.head()`

Rotate axis labels

Question:

Answers:

Imports and Sample DataFrame

pandas.DataFrame.plot with subplots=True

plt.subplots

seaborn.relplot

DataFrmames

df.head()

dfl.head()

`pandas.DataFrame.plot` with `subplots=True`

`plt.subplots`

`seaborn.relplot`

`df.head()`

`dfl.head()`