Writing your own non-parametrized ‘verb’

R:

rc = function(df) ( df[rev(colnames(df)])
mtcars %>% rc()

Any function taking a df as first parameter is a verb.

The python example is slightly more ‘practical’ in that it’s not an entirely trivial function.

prelude:

def ints_to_floats(df):
  return df.assign(**{x[0]: x[1] for x in df.select_dtypes(int).astype(float).items()})

pandas::

ints_to_floats(mtcars)

plydata:

no documentation on custom verbs

dplython:

@dp.ApplyToDataframe
def ints_to_floats():
  return lambda df: df.assign(**{x[0]: x[1] for x in df.select_dtypes(int).astype(float).items()})

dp.DplyFrame(mtcars) >> ints_to_floats()

Undocumented. Note that custom verbs (and many dplython verbs, but not all of them) need to start with a dp.DplyFrame object, not a pd.DataFrame. Mutate is one exception

dfply:

@dp.dfpipe
def ints_to_floats(df):
  return df.assign(**{x[0]: x[1] for x in df.select_dtypes(int).astype(float).items()})
mtcars >> ints_to_floats()

dfpipe decorator is well documented

dppd:

#one more import
from dppd register_verb
dp, X = dppd()()

@register_verb()
def ints_to_floats(df):
  return df.assign(**{x[0]: x[1] for x in df.select_dtypes(int).astype(float).items()})
dp(mtcars).ints_to_floats().pd