如何使用 Seaborn 在同一图上绘制多个直方图

Question

With matplotlib, I can make a histogram with two datasets on one plot (one next to the other, not overlay).

import matplotlib.pyplot as plt
import random

x = [random.randrange(100) for i in range(100)]
y = [random.randrange(100) for i in range(100)]
plt.hist([x, y])
plt.show()

This yields the following plot.

However, when I try to do this with seabron;

import seaborn as sns
sns.distplot([x, y])

I get the following error:

ValueError: color kwarg must have one color per dataset

So then I try to add some color values:

sns.distplot([x, y], color=['r', 'b'])

And I get the same error. I saw this post on how to overlay graphs, but I would like these histograms to be side by side, not overlay.

And looking at the docs it doesn't specify how to include a list of lists as the first argument 'a'.

How can I achieve this style of histogram using seaborn?

Answer 1

If I understand you correctly you may want to try something this:

fig, ax = plt.subplots()
for a in [x, y]:
    sns.distplot(a, bins=range(1, 110, 10), ax=ax, kde=False)
ax.set_xlim([0, 100])

Which should yield a plot like this:

UPDATE :

Looks like you want 'seaborn look' rather than seaborn plotting functionality. For this you only need to:

import seaborn as sns
plt.hist([x, y], color=['r','b'], alpha=0.5)

Which will produce:

Answer 2

Merge x and y to DataFrame, then use histplot with multiple='dodge' and hue option:

import matplotlib.pyplot as plt
import pandas as pd
import random

x = [random.randrange(100) for i in range(100)]
y = [random.randrange(100) for i in range(100)]
df = pd.concat(axis=0, ignore_index=True, objs=[
    pd.DataFrame.from_dict({'value': x, 'name': 'x'}),
    pd.DataFrame.from_dict({'value': y, 'name': 'y'})
])
fig, ax = plt.subplots()
sns.histplot(data=df, x='value', hue='name', multiple='dodge', bins=range(1, 110, 10), ax=ax)
ax.set_xlim([0, 100])

Here is the plot result.