Plot multiple boxplot in one graph in pandas or matplotlib?

It easy using pandas:

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

col1 = np.random.random(10)
col2 = np.random.random(10)

DF = pd.DataFrame({'col1': col1, 'col2': col2})

ax = DF[['col1', 'col2']].plot(kind='box', title='boxplot', showmeans=True)

plt.show()

Note that when using Pandas for this, the last command (ax = DF[[...) opens a new figure. I'm still looking for a way to combine this with existing subplots.

To plot multiple boxplots on one matplotlib graph you can pass a list of data arrays to boxplot, as in:

import numpy as np
import matplotlib.pyplot as plt

x1 = 10*np.random.random(100)
x2 = 10*np.random.exponential(0.5, 100)
x3 = 10*np.random.normal(0, 0.4, 100)
plt.boxplot ([x1, x2, x3])

The only thing I am not sure of is if you want each boxplot to have a different color etc. Generally it won't plot in different colour

Use return_type='axes' to get a1.boxplot to return a matplotlib Axes object. Then pass that axes to the second call to boxplot using ax=ax. This will cause both boxplots to be drawn on the same axes.

a1=a[['kCH4_sync','week_days']]
ax = a1.boxplot(by='week_days', meanline=True, showmeans=True, showcaps=True, 
                showbox=True, showfliers=False, return_type='axes')
a2 = a[['CH4_sync','week_days']]
a2.boxplot(by='week_days', meanline=True, showmeans=True, showcaps=True, 
           showbox=True, showfliers=False, ax=ax)