Custom xlabel rotation issue with pandas plot when using secondary_y

Question

I want to show the x labels rotated 45 degrees. I tired the following code, but it still shows the x labels with 0 rotation.

How can the labels be rotated?

df_final = pd.DataFrame({'Count':[8601,188497,808,7081,684,15601,75,12325],
                         'Average': [0.128,0.131,0.144,.184,.134,.152,0.139,0.127]})
width = 0.8
df_final['Count'].plot(kind='bar', width = width)
df_final['Average'].plot(secondary_y=True)
ax = plt.gca()
ax.set_xticklabels(['One', 'Two', 'Three', 'Four', 'Five','Six','Seven','Eight'],rotation = 45)
plt.show()

Asked By: John

||

Source

Answer 1

Just change the place of ax = plt.gca() Can you try below code :

df_final = pd.DataFrame({'Count':[8601,188497,808,7081,684,15601,75,12325],
                         'Average': [0.128,0.131,0.144,.184,.134,.152,0.139,0.127]})
width = 0.8
ax = plt.gca()
df_final['Count'].plot(kind='bar', width = width)
df_final['Average'].plot(secondary_y=True)
ax.set_xticklabels(['One', 'Two', 'Three', 'Four', 'Five','Six','Seven','Eight'],rotation = 45)
plt.show()

Answered By: Ugur Yigit

Answer 2

pandas.DataFrame.plot returns matplotlib.axes.Axes. As such, assign the Axes of the first plot to a variable, ax.
- ax = plt.gca() is not required, but would go directly before df_final['Average'].plot(...) if used.
The settings of the second plot take precedence, therefore the rotation should be set with rot=45 in the second plot call, or in set_xticklabels.
Also see Add label values to bar chart and line chart for adding labels.
Tested in python 3.11, pandas 1.5.3, matplotlib 3.7.0

Sample Data and Setup

import pandas as pd

df_final = pd.DataFrame({'Count': [8601, 188497, 808, 7081, 684, 15601, 75, 12325],
                         'Average': [0.128, 0.131, 0.144, 0.184, 0.134, 0.152, 0.139, 0.127]})

width = 0.8

labels = ['One', 'Two', 'Three', 'Four', 'Five', 'Six', 'Seven', 'Eight']

Option 1

# assign the plot to ax
ax = df_final['Count'].plot(kind='bar', width=width, figsize=(9, 6), legend=True)

# place the secondary plot on ax
df_final['Average'].plot(secondary_y=True, ax=ax, color='r', legend=True)  # optionally add rot=45 here

# set the custom xtick labels and rotate
_ = ax.set_xticklabels(labels, rotation=45)  # remove rotation=45 if using rot=45 in the previous line

Option 2

# set the index values to the labels, providing the order corresponds to the DataFrame
df_final.index = labels

# initial plot
ax = df_final['Count'].plot(kind='bar', width=width, figsize=(9, 6), legend=True)

# secondary plot and specify rotation
df_final['Average'].plot(secondary_y=True, ax=ax, rot=45, color='r', legend=True)

Option 3

Create the DataFrame with a custom index using the index parameter, and then plot like Option 2 without df_final.index = labels.

df_final = pd.DataFrame({'Count': [8601, 188497, 808, 7081, 684, 15601, 75, 12325],
                         'Average': [0.128, 0.131, 0.144, 0.184, 0.134, 0.152, 0.139, 0.127]},
                        index=labels)

Answered By: Trenton McKinney

Custom xlabel rotation issue with pandas plot when using secondary_y

Question:

Answers:

Sample Data and Setup

Option 1

Option 2

Option 3