python - Select multiple groups from pandas groupby object

Question

I am experimenting with the groupby features of pandas, in particular

gb = df.groupby('model')
gb.hist()

Since gb has 50 groups the result is quite cluttered, I would like to explore the result only for the first 5 groups.

I found how to select a single group with groups or get_group (How to access pandas groupby dataframe by key), but not how to select multiple groups directly. The best I could do is :

groups = dict(list(gb))
subgroup = pd.concat(groups.values()[:4])
subgroup.groupby('model').hist()

Is there a more direct way?

Answer 1

It'd be easier to just filter your df first and then perform the groupby:

In [155]:

df = pd.DataFrame({'model':np.random.randint(1,10,100), 'value':np.random.randn(100)})
first_five = df['model'].sort(inplace=False).unique()[:5]
gp = df[df['model'].isin(first_five)].groupby('model')
gp.first()
Out[155]:
          value
model          
1     -0.505677
2      1.217027
3     -0.641583
4      0.778104
5     -1.037858