Is there a way to create a combined bar and line plot on a single graph with separate Y axes?

I have two sets of data that share a common index, and I would like to display the first set as a barplot and the second set as a line plot on the same graph. Currently, I am using a method similar to the one shown below.

ax = pt.a.plot(alpha = .75, kind = 'bar')
ax2 = ax.twinx()
ax2.plot(ax.get_xticks(), pt.b.values, alpha = .75, color = 'r')

The resulting graph looks something like this:

https://i.stack.imgur.com/KgYEP.png

While the image is visually appealing, it's not quite perfect. The issue I'm facing is that ax.twinx() appears to overlay a new canvas on top of the existing one, causing white lines to be visible over the barplot.

Is there a way to create this plot without these unwanted white lines?

pythonpandasmatplotlibseabornbar-chart

Answer №1

If you want to create a dual y-axis plot with seaborn, you can utilize the twinx() method. This allows you to have separate y-axes for different plots such as lineplot and barplot. To customize the style of the plot (default is darkgrid), you can use the set_style method to choose a different theme. Setting style=None will give you a white background without gridlines, or you can experiment with other themes like whitegrid. If you need more control over the gridlines, you can adjust them at the axis level using ax2.grid(False).

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

matplotlib.rc_file_defaults()
ax1 = sns.set_style(style=None, rc=None )

fig, ax1 = plt.subplots(figsize=(12,6))

sns.lineplot(data = df['y_var_1'], marker='o', sort = False, ax=ax1)
ax2 = ax1.twinx()

sns.barplot(data = df, x='x_var', y='y_var_2', alpha=0.5, ax=ax2)

https://i.stack.imgur.com/gCnI6.png

Answer №2

To remove the grid lines of the second axis, simply add ax2.grid(False) to your code. Keep in mind that the y-ticks of the second axis will not align with those of the first y-axis, as shown below:

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

fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.plot(pd.Series(np.random.uniform(0,1,size=10)), color='g')
ax2 = ax1.twinx()
ax2.plot(pd.Series(np.random.uniform(0,17,size=10)), color='r')
ax2.grid(False)
plt.show()

https://i.stack.imgur.com/t84aD.png

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