CODEWITHSUNDEEP
pythonmatplotlib
steven
steven

Reputation: 2519

customize matplotlib ticklabels individually

Please consider the following example in which I want to change the weight of label "C" to bold. 

df = pd.DataFrame(data={'value': [3, 5, 7, 4, 5]},
                  index=list('ABCDE'))

fig, ax = plt.subplots()
df.plot.barh(ax=ax)

enter image description here

Many examples I've seen (e.g., tick_params and set_yticklabels) change all ticklabels or simply replace a label without formatting.

Is there a way to customize it individually?

Upvotes: 0

Views: 118

Answers (1)

Sheldore
Sheldore

Reputation: 39052

This is one way to do so:

  • Traverse through the default tick-labels,
  • Modify the required label to be bold faced,
  • Reassign the tick-labels.
from matplotlib import rc
import pandas as pd
import matplotlib.pyplot as plt

rc('text', usetex=True)

df = pd.DataFrame(data={'value': [3, 5, 7, 4, 5]},
                  index=list('ABCDE'))

fig, ax = plt.subplots()
df.plot.barh(ax=ax)

fig.canvas.draw()
new_labels = []
to_modify = 'C'

for lab in ax.get_yticklabels():
    txt = lab.get_text()
    if txt == to_modify:
        new_labels.append(r'$\textbf{%s}$' %txt) # append bold face text
    else:    
        new_labels.append(txt) # append normal text

ax.set_yticklabels(new_labels)

enter image description here

Alternative as suggested by ImportanceOfBeingEarnest : set_fontweight only works if not using latex (TeX rendering).

fig, ax = plt.subplots()
df.plot.barh(ax=ax)

to_modify = 'C'

for lab in ax.get_yticklabels():
    if lab.get_text() == to_modify:
      lab.set_fontweight('bold')

Upvotes: 1

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