Pandas plot subplots of a 'group by' result

Question

I struggle with my (poor) Pandas knowledge, as I try to get a bar plot on a hierachial index by a group by operation.

My data look like this

id, val, cat1, cat2

Then I create a hierachical index:

df_group = df_len.groupby(['cat1','cat2'])

I would like to get a hbar plot per cat1 object that lists all cat2 objects that lists the values of all cat1 objects within.

None of my approaches worked:

df_group.plot(...)
for name, group in df_group: .... group.plot(...)
df_group.xs(...) experiments

The result should look somewhat like this one enter image description here

I guess I just lack of knowledge of pandas, matplotlib, ... -internals and it's not that difficult to plot a few 100 items (cat2<10, cat1=30)

.

b10n · Accepted Answer · 2014-09-29 23:52:59Z

2

I'd recommend using seaborn to do this type of faceted plot. Doing it in matplotlib is very tricky as the library is quite low level. Seaborn excels at this use case.

answered Sep 29, 2014 at 23:52

b10n

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MaM Over a year ago

I tried seaborn, but without any luck in my case. But it seems to be a nice piece of code for higher dim data :)

MaM · Accepted Answer · 2014-10-06 15:39:37Z

2

Ok guys, so here it's how I solved it finally:

dfc = df_len.groupby(['cat1','cat2']).count().reset_index()
dfp=dfc.pivot(index="cat1",columns="cat2")
dfp.columns = dfp.columns.get_level_values(1)
dfp.plot(kind='bar', figsize=(15, 5), stacked=True);

In short: I used a pivot table to transpose my matrix and then I was able to plot the single cols automaticly, at example 2 here.

answered Oct 6, 2014 at 15:39

MaM

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Comments

CT Zhu · Accepted Answer · 2014-09-30 15:25:46Z

1

Not so tricky in matplotlib, see:

In [54]:

print df
  cat1  cat2       val
0    A     1  0.011887
1    A     2  0.880121
2    A     3  0.034244
3    A     4  0.530230
4    B     1  0.510812
5    B     2  0.405322
6    B     3  0.406259
7    B     4  0.406405
In [55]:

col_list = ['r', 'g']
ax = plt.subplot(111)
for (idx, (grp, val)) in enumerate(df.groupby('cat1')):
    ax.bar(val.cat2+0.25*idx-0.25, 
           val.val, width=0.25,  
           color=col_list[idx], 
           label=grp)
plt.legend()

enter image description here

answered Sep 30, 2014 at 15:25

CT Zhu

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1 Comment

MaM Over a year ago

Nice idea, but I solved it finally with pure pandas and avoided the matplot tricks. But anyway, thanks for your help!

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