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

plotting 2 distplots or scatterplots in subplot works great:

import matplotlib.pyplot plt import numpy np import seaborn sns import pandas pd %matplotlib inline  # create df x = np.linspace(0, 2 * np.pi, 400) df = pd.dataframe({'x': x, 'y': np.sin(x ** 2)})  # 2 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() 

but when same lmplot instead of either of other types of charts error:

attributeerror: 'axessubplot' object has no attribute 'lmplot'

is there way plot these chart types side side?

you error because matplotlib , objects unaware of seaborn functions.

pass axes objects (i.e., ax1 , ax2) seaborn.regplot or can skip defining , use col kwarg of seaborn.lmplot

with same imports, pre-defining axes , using regplot looks 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 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) 

using lmplot requires dataframe tidy. continuing code above:

tidy = (     df.stack() # pull columns row variables          .to_frame() # convert resulting series dataframe       .reset_index() # pull resulting multiindex columns       .rename(columns={0: 'val'}) # rename unnamed column ) sns.lmplot(x='obs', y='val', col='vars', hue='vars', data=tidy)