notes/pl/py/libfws/ml/pandas/features/groupby.txt

http://pandas.pydata.org/pandas-docs/stable/groupby.html
https://www.shanelynn.ie/summarising-aggregation-and-grouping-data-in-python-pandas/
https://www.datacamp.com/community/tutorials/pandas-split-apply-combine-groupby
https://www.datacamp.com/community/tutorials/pandas-multi-index

groupby(...
    as_index=False,
    sort=True,
    level=0,
    level='second',
    level=['first', 'second'],
).reset_index()

for name, group in dfallgrouped:
    print(name)
    print(group.iloc[2:-2])

dfallgrouped.apply(lambda grp: grp.iloc[2:-2])

.groups
.get_group(...)
.first()
.mean()
.aggregate(np.sum)
    .sum()
.sum().reset_index()
.agg([np.sum, np.mean, np.std])
# agg by one column
groupby(...)['C'].agg({'sum':np.sum, 'mean':np.mean})
# ... by distinct columns
groupby(...).agg({'sum':np.sum, 'mean':np.mean})

mean = lambda x: (x-np.mean(x))
.transform(mean)

df.loc[df.groupby('A')['B'].idxmin()]
df.sort('B').groupby('A'), as_index=False).first()