How to plot multiple columns into a single seaborn boxenplot

Question

I have my two graphs on top of each other and I would like to put them next to each other but I don't know how to do it?

code :

import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_theme(style="whitegrid")
boxenplot_graph = sns.boxenplot(x=expeditions["nbre_members"], color = "r")
boxenplot_graph2 = sns.boxenplot(x=expeditions["hired_staff"],color = "b")
plt.xlabel("Nombre de members/hired_staff")
plt.title("Répartition du nombre de membres/hired_staff")
#plt.gca().legend(('membres', 'morts'))
plt.legend(["members", "hired_staff"],['rouge', 'bleu'])

Answer 1

• Convert the columns to a long form with .melt
• See seaborn.boxenplot
  • Plot by specifying one axis for the values and the other for the category column. hue= can be used to visualize a third categorical column.
• No legend is required (for this case) because the labels for each are on the axis, so having a legend it redundant
• The categorical axis labels can be changed in a number of ways.
  • Change the column name before melting (use .rename)
  • Change the values in the column after melting (use .map)
  • Change the ticklabel of the plot (p.set_yticklabels(['Total Bill', 'Tips'])
• Tested in python 3.9.7, pandas 1.3.4, matplotlib 3.5.0, seaborn 0.11.2

dfm = expeditions[["nbre_members", "hired_staff"]].melt()
sns.boxenplot(data=dfm, x='value', y='variable')

Working Example

import seaborn as sns
import matplotlib.pyplot as plt

# sample data for wide data
tips = sns.load_dataset('tips')

# display(tips.head(3))
   total_bill   tip     sex smoker  day    time  size
0       16.99  1.01  Female     No  Sun  Dinner     2
1       10.34  1.66    Male     No  Sun  Dinner     3
2       21.01  3.50    Male     No  Sun  Dinner     3

# convert two columns to a long form
dfm = tips[['total_bill', 'tip']].melt()

# display(dfm.head(3))
     variable  value
0  total_bill  16.99
1  total_bill  10.34
2  total_bill  21.01

# plot
fig, ax = plt.subplots(figsize=(6, 4))
p = sns.boxenplot(data=dfm, x='value', y='variable', ax=ax)
p.set(ylabel='My yLabel', xlabel='My xLabel', title='My Title')
p.set_yticklabels(['Total Bill', 'Tips'])
plt.show()

Given a 3rd column

• This option uses a 3rd column for hue=

# melt columns and have an id variable
dfm = tips[['total_bill', 'tip', 'smoker']].melt(id_vars='smoker')

# display(dfm.head(3))
  smoker    variable  value
0     No  total_bill  16.99
1     No  total_bill  10.34
2     No  total_bill  21.01

# plot
fig, ax = plt.subplots(figsize=(6, 4))
p = sns.boxenplot(data=dfm, x='value', y='variable', hue='smoker', ax=ax)
p.set(ylabel='My yLabel', xlabel='My xLabel')
plt.show()

Answer 2

use subplots if you had two different datasets expeditions1 and expeditions2

import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns
expeditions1=np.random.random_integers(1, 100, size=500)
expeditions2=np.random.random_integers(1, 1000, size=500)
sns.set_theme(style="whitegrid")
fig,ax=plt.subplots(2,figsize=(10,10))
boxenplot_graph = sns.boxenplot(y=expeditions1, color = "r",ax=ax[0])
ax[0].set_title("One boxenplot")
boxenplot_graph2 = sns.boxenplot(y=expeditions2,color = "b",ax=ax[1])
plt.xlabel("hired staff")
ax[1].set_title("Two boxenplot")
#plt.gca().legend(('membres', 'morts'))
plt.legend(["members", "hired_staff"],['rouge', 'bleu'])