Subplot for seaborn boxplot

Solution 1:

We create the figure with the subplots:

f, axes = plt.subplots(1, 2)

Where axes is an array with each subplot.

Then we tell each plot in which subplot we want them with the argument ax.

sns.boxplot(  y="b", x= "a", data=df,  orient='v' , ax=axes[0])
sns.boxplot(  y="c", x= "a", data=df,  orient='v' , ax=axes[1])

And the result is:

Solution 2:

names = ['b', 'c']
fig, axes = plt.subplots(1,2)

for i,t in enumerate(names):
    sns.boxplot(y=t, x="a", data=df, orient='v', ax=axes[i % 2])

Example:

names = ['b', 'c']
fig, axes = plt.subplots(1,2)
sns.set_style("darkgrid")
flatui = ["#95a5a6", "#34495e"]

for i,t in enumerate(names):
    sns.boxplot(y=t, x= "a", data=df, orient='v', ax=axes[i % 2], palette=flatui)

Solution 3:

If you wish to iterate through multiple different subplots, use plt.subplots:

import matplotlib.pyplot as plt

# Creating subplot axes
fig, axes = plt.subplots(nrows,ncols)

# Iterating through axes and names
for name, ax in zip(names, axes.flatten()):
    sns.boxplot(y=name, x= "a", data=df, orient='v', ax=ax)

Working example:

import numpy as np

# example data
df = pd.DataFrame({'a' :['one','one','two','two','one','two','one','one','one','two'], 
                   'b': np.random.randint(1,8,10), 
                   'c': np.random.randint(1,8,10),
                   'd': np.random.randint(1,8,10),
                   'e': np.random.randint(1,8,10)})

names = df.columns.drop('a')
ncols = len(names)
fig, axes = plt.subplots(1,ncols)

for name, ax in zip(names, axes.flatten()):
    sns.boxplot(y=name, x= "a", data=df, orient='v', ax=ax)
    
plt.tight_layout()