bar plot a multiheader dataframe in a desired format

Question

I have the following DataFrame:

data = {('Case1', 'A'): {'One': 0.96396415, 'Two': 0.832049574, 'Three': 0.636568627, 'Four': 0.765846157},
        ('Case1', 'B'): {'One': 0.257496625, 'Two': 0.984418254, 'Three': 0.018891398, 'Four': 0.440278509},
        ('Case1', 'C'): {'One': 0.512732941, 'Two': 0.622697929, 'Three': 0.731555346, 'Four': 0.031419349},
        ('Case2', 'A'): {'One': 0.736783294, 'Two': 0.460765675, 'Three': 0.078558864, 'Four': 0.566186283},
        ('Case2', 'B'): {'One': 0.921473211, 'Two': 0.274749932, 'Three': 0.312766018, 'Four': 0.159229808},
        ('Case2', 'C'): {'One': 0.146389032, 'Two': 0.893299471, 'Three': 0.536288712, 'Four': 0.775763286},
        ('Case3', 'A'): {'One': 0.351607026, 'Two': 0.041402396, 'Three': 0.924265706, 'Four': 0.639154727},
        ('Case3', 'B'): {'One': 0.966538215, 'Two': 0.658236148, 'Three': 0.473447279, 'Four': 0.545974617},
        ('Case3', 'C'): {'One': 0.036585457, 'Two': 0.279443317, 'Three': 0.407991168, 'Four': 0.101083315}}

pd.DataFrame(data=data)

	Case1	Case1	Case1	Case2	Case2	Case2	Case3	Case3	Case3
	A	B	C	A	B	C	A	B	C
One	0,963964	0,257497	0,512733	0,736783	0,921473	0,146389	0,351607	0,966538	0,036585
Two	0,83205	0,984418	0,622698	0,460766	0,27475	0,893299	0,041402	0,658236	0,279443
Three	0,636569	0,018891	0,731555	0,078559	0,312766	0,536289	0,924266	0,473447	0,407991
Four	0,765846	0,440279	0,031419	0,566186	0,15923	0,775763	0,639155	0,545975	0,101083

There are 2 header rows.

In the end i need a plot like the following (which i created in excel).
Another solution would be a seperate plot for every Case, instead of all in one.

What i tried so far is:

df.T.melt(ignore_index=False)

to get the DataFrame in a format like i used in excel.
But from there i could not figure any solution to get the right plot. Maybe the transpose/melt is not even necessary.

Can anyone give me a hint on how to achieve the desired plot?

Asked By: Paul

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Source

Answer 1

Given your data, if it is in Excel, one would read it like this:

import pandas as pd
df = pd.read_excel('values.xlsx', index_col=0, header=[0,1])

To plot something very similar to what you would like:

long_df = df.T.stack().reset_index()
long_df.columns = ['cases', 'subcases', 'observations', 'value']
transformed = long_df.pivot_table(
    index=['cases', 'observations'],
    columns='subcases',
    values='value',
    sort=False)
transformed.plot(kind='bar')

Explaining how it works:

long_df is a df normalized to a ‘long’ format using stack function.
pivot data to get it in a correct orientation for simple plotting
plot in matplotlib using .plot method and bar option.

Answered By: Kirill Setdekov

Answer 2

Make sure to reshape your dataframe first so the two levels of the x-axis be as a MultiIndex.

df = df.T.stack().unstack(level=1)

Then make the plot this way (highly inspired by @gyx-hh answer) :

def plot_function(x, ax):
    ax = graph[x]
    ax.set_xlabel(x)
    return df.xs(x).plot.bar(ax=ax, legend=False, rot=0)

fig, axes = plt.subplots(nrows=1, ncols=len(df.index.levels[0]),
                         sharey=True, figsize=(16, 4))

graph = dict(zip(df.index.levels[0], axes))
plots = list(map(lambda x: plot_function(x, graph[x]), graph))
ax.tick_params(axis="both", which="both", length=0)
fig.subplots_adjust(wspace=0)

plt.legend()
plt.show();

Output :

Answered By: Timeless

bar plot a multiheader dataframe in a desired format

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