How to plot 2 seaborn lmplots side-by-side?

samthebrand picture samthebrand · Oct 10, 2015 · Viewed 54.6k times · Source

Plotting 2 distplots or scatterplots in a subplot works great:

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

# create df
x = np.linspace(0, 2 * np.pi, 400)
df = pd.DataFrame({'x': x, 'y': np.sin(x ** 2)})

# Two subplots
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(df.x, df.y)
ax1.set_title('Sharing Y axis')
ax2.scatter(df.x, df.y)

plt.show()

Subplot example

But when I do the same with an lmplot instead of either of the other types of charts I get an error:

AttributeError: 'AxesSubplot' object has no attribute 'lmplot'

Is there any way to plot these chart types side by side?

Answer

Paul H picture Paul H · Oct 13, 2015

You get that error because matplotlib and its objects are completely unaware of seaborn functions.

Pass your axes objects (i.e., ax1 and ax2) to seaborn.regplot or you can skip defining those and use the col kwarg of seaborn.lmplot

With your same imports, pre-defining your axes and using regplot looks like this:

# create df
x = np.linspace(0, 2 * np.pi, 400)
df = pd.DataFrame({'x': x, 'y': np.sin(x ** 2)})
df.index.names = ['obs']
df.columns.names = ['vars']

idx = np.array(df.index.tolist(), dtype='float')  # make an array of x-values

# call regplot on each axes
fig, (ax1, ax2) = plt.subplots(ncols=2, sharey=True)
sns.regplot(x=idx, y=df['x'], ax=ax1)
sns.regplot(x=idx, y=df['y'], ax=ax2)

enter image description here

Using lmplot requires your dataframe to be tidy. Continuing from the code above:

tidy = (
    df.stack() # pull the columns into row variables   
      .to_frame() # convert the resulting Series to a DataFrame
      .reset_index() # pull the resulting MultiIndex into the columns
      .rename(columns={0: 'val'}) # rename the unnamed column
)
sns.lmplot(x='obs', y='val', col='vars', hue='vars', data=tidy)

enter image description here