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
%
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()
Regplots with Hue