Boxplot : custom width in seaborn

Question

I am trying to plot boxplots in seaborn whose widths depend upon the log of the value of x-axis. I am creating the list of widths and passing it to the widths=widths parameter of seaborn.boxplot.

However, I am getting that

raise ValueError(datashape_message.format("widths"))
ValueError: List of boxplot statistics and `widths` values must have same the length

When I debugged and checked there is just one dict in boxplot statistics, whereas I have 8 boxplots. Cannot Exactly figure out where the problem lies.

I am using pandas data frame and seaborn for plotting.

Answer 1

Seaborn's boxplot doesn't seem to understand the widths= parameter.

Here is a way to create a boxplot per x value via matplotlib's boxplot which does accept the width= parameter. The code below supposes the data is organized in a panda's dataframe.

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

df = pd.DataFrame({'x': np.random.choice([1, 3, 5, 8, 10, 30, 50, 100], 500),
                   'y': np.random.normal(750, 20, 500)})
xvals = np.unique(df.x)
positions = range(len(xvals))
plt.boxplot([df[df.x == xi].y for xi in xvals],
            positions=positions, showfliers=False,
            boxprops={'facecolor': 'none'}, medianprops={'color': 'black'}, patch_artist=True,
            widths=[0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
means = [np.mean(df[df.x == xi].y) for xi in xvals]
plt.plot(positions, means, '--k*', lw=2)
# plt.xticks(positions, xvals) # not needed anymore, as the xticks are set by the swarmplot
sns.swarmplot('x', 'y', data=df)
plt.show()

A related question asked how to set the box's widths depending on group size. The widths can be calculated as some maximum width multiplied by each group's size compared to the size of the largest group.

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

y_true = np.random.normal(size=100)
y_pred = y_true + np.random.normal(size=100)
df = pd.DataFrame({'y_true': y_true, 'y_pred': y_pred})
df['y_true_bin'] = pd.cut(df['y_true'], range(-3, 4))

sns.set()
fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(12, 5))
sns.boxplot(x='y_true_bin', y='y_pred', data=df, color='lightblue', ax=ax1)

bins, groups = zip(*df.groupby('y_true_bin')['y_pred'])
lengths = np.array([len(group) for group in groups])
max_width = 0.8
ax2.boxplot(groups, widths=max_width * lengths / lengths.max(),
            patch_artist=True, boxprops={'facecolor': 'lightblue'})
ax2.set_xticklabels(bins)
ax2.set_xlabel('y_true_bin')
ax2.set_ylabel('y_pred')
plt.tight_layout()
plt.show()