How To Plot Multiple Histograms On Same Plot With Seaborn

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 random  import matplotlib.pyplot as plt import pandas as pd import seaborn as sns  x = [random.randrange(100) for _ in range(100)] y = [random.randrange(100) for _ 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])