Iterate over groups / build a new dataframe from dataframe of groups

R:

dfnrow = function(df) (data.frame(count=nrow(df)))
mtcars %>% group_by(cyl) %>%  do(dfnrow(.))

pandas:

def something(grp):
    return pd.DataFrame({'count': [len(grp)]})
pd.concat([something(group).assign(cyl=idx) for idx, group in mtcars.groupby('cyl')],axis=0)

pyldata:

mtcars >> dp.group_by('cyl') >> dp.do(something)

No iterator over groups

dpylython:

No do, no group iterator

dfply version 1:

mtcars >> dp.group_by('cyl') >> dfply.dfpipe(something)()

Approach 1: turn something into a verb.

dfply version 2:

@dfply.dfpipe
def do(df, func, *args, **kwargs):
    return func(df, *args, **kwargs)
mtcars >> dp.group_by('cyl') >> do(something)

Approach 2: introduce do verb.

dppd:

dp(mtcars).groupby('cyl').do(something).pd

or

for idx, sub_df in dp(mtcars).groupby('cyl').itergroups():
  print(idx, something(sub_df))

dppd has a group iterator.