Apparently this is on the wishlist.
Here's an example that is referred to in the post that does what you want, but with a couple of functions.
However, a quick solution would be to just plot two bar plots side-by-side and customising the graph a little bit.
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
#create multindex dataframe
arrays = [['Fruit', 'Fruit', 'Fruit', 'Veggies', 'Veggies', 'Veggies'],
['Bananas', 'Oranges', 'Pears', 'Carrots', 'Potatoes', 'Celery']]
index = pd.MultiIndex.from_tuples(list(zip(*arrays)))
df = pd.DataFrame(np.random.randint(10, 50, size=(1, 6)), columns=index)
#plotting
fig, axes = plt.subplots(nrows=1, ncols=2, sharey=True, figsize=(14 / 2.54, 10 / 2.54)) # width, height
for i, col in enumerate(df.columns.levels[0]):
print(col)
ax = axes[i]
df[col].T.plot(ax=ax, kind='bar', width=.8)
ax.legend_.remove()
ax.set_xlabel(col, weight='bold')
ax.yaxis.grid(b=True, which='major', color='black', linestyle='--', alpha=.4)
ax.set_axisbelow(True)
for tick in ax.get_xticklabels():
tick.set_rotation(0)
#make the ticklines invisible
ax.tick_params(axis=u'both', which=u'both', length=0)
plt.tight_layout()
# remove spacing in between
fig.subplots_adjust(wspace=0) # space between plots
plt.show()
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