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

Question

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()

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?

Paul H · Accepted Answer · 2015-10-12 23:28:58Z

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)

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)

Is there another way (meanwhile) to plot lmplot side by side? In my case, I don't wanna' split the hue into different subplots but put those lmplots themselves into subplots next to each other. I can't find a way how to do so..
@Ben I don't understand your comment. Did you try removing the hue parameter from the call to lmplot?
Is there a way to combine two lmplots (not regplots) each with multiple axes? For example, I have two lmplots with 1 row and 4 columns. I hope to combine them to a 2 row by 4 column plot
@XinNiu combine your datasets, and use the row parameter in lmplot

RMS · Accepted Answer · 2024-06-25 09:37:38Z

EDIT: It is now possible to use hue by simply passing it as an argument to lmplot

from API documentation:

sns.lmplot(data=penguins, x="bill_length_mm", y="bill_depth_mm", hue="species")

If the intention of using lmplot is to use hue for two different sets of variables, regplot may not be sufficient without some tweaks. In order to use of seaborn's lmplot hue argument in two side-by-side plots, one possible solution is:

def hue_regplot(data, x, y, hue, palette=None, **kwargs): from matplotlib.cm import get_cmap regplots = [] levels = data[hue].unique() if palette is None: default_colors = get_cmap('tab10') palette = {k: default_colors(i) for i, k in enumerate(levels)} for key in levels: regplots.append( sns.regplot( x=x, y=y, data=data[data[hue] == key], color=palette[key], **kwargs ) ) return regplots

This function give result similar to lmplot (with hue option), but accepts the ax argument, necessary for creating a composite figure. An example of usage is

import matplotlib.pyplot as plt import numpy as np import seaborn as sns import pandas as pd %matplotlib inline rnd = np.random.default_rng(1234567890) # create df x = np.linspace(0, 2 * np.pi, 400) df = pd.DataFrame({'x': x, 'y': np.sin(x ** 2), 'color1': rnd.integers(0,2, size=400), 'color2': rnd.integers(0,3, size=400)}) # color for exemplification # 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) hue_regplot(data=df, x='x', y='y', hue='color1', ax=ax1) hue_regplot(data=df, x='x', y='y', hue='color2', ax=ax2) plt.show()

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