CODEWITHSUNDEEP
pythonpandasdataframematplotlibplot
user10730937
user10730937

Reputation:

Stacked plots from a multi-index data

I know how to plot something like this:

               SEASON1  SEASON2  SEASON3
area                                    
A   299.0  2.0  257.0
B   13.0  33.0  198.0
C   22044.0  2.0  22.0

Using 

df.plot(kind='bar', stacked=True, rot=90, edgecolor='black')
df.T.plot(kind='bar', stacked=True, rot=0, edgecolor='black')

Resulting in:

stacked

transposed stacked

I'm having hard time to obtain the same (or even better looking) plots for the following df which is representing the original df but made more elegantly here.

Upvotes: 1

Views: 161

Answers (1)

IMCoins
IMCoins

Reputation: 3306

What you want to do is to unstack your dataframe, and change the name of the columns.

You can do so by doing : 

df.unstack()
  .rename(columns = {
            "2016Q1" : "Season 1",
            "2016Q2" : "Season 2",
            "2016Q3" : "Season 3",
        })

You can find examples on the documentation about what unstack does, and how it is doing it. As for the rename method, it takes a mapping to convert your names from something to something else.

I didn't try to make your example work, but I took an example from the unstack documentation above.

index = pd.MultiIndex.from_tuples([('one', 'a'), ('one', 'b'),
                                   ('two', 'a'), ('two', 'b')])

df = pd.DataFrame( np.arange(1.0, 5.0), index=index, columns=['hi'])
print(df)
#         hi
# one a  1.0
#     b  2.0
# two a  3.0
#     b  4.0

df = df.unstack(level = -1)
       .rename(columns = {
            "a" : "Season 1",
            "b" : "Season 2"
        })
print(df)
#           hi         
#     Season 1 Season 2
# one      1.0      2.0
# two      3.0      4.0

There could be a better way to handle the "hi" above your DataFrame but you can just select it, and it'll disappear.

print( s['hi'] )
     Season 1  Season 2
one       1.0       2.0
two       3.0       4.0

Upvotes: 1

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