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

pipe() # to DataFrame
apply() # to rows/columns
applymap() # to elements

(df.pipe(h)
    .pipe(g, arg1=1)
    .pipe(f, arg2=2, arg3=3)
)
# is the same as
f(g(h(df), arg1=1), arg2=2, arg3=3)

# by columns
df.apply(lambda x: x/sum(x))
# by rows
df.apply(lambda x: x/sum(x), axis=1)


map()
# add country-column based on city
d = {u'London':u'GB', u'Moscow':u'RUS', u'Paris':u'FR'}
df['country'] = df['city'].map(d)

df.columns = map(str.lower, df.columns) # lowercase column names


# rename after aggregate

https://stackoverflow.com/questions/44635626/pandas-aggregation-warning-futurewarning-using-a-dict-with-renaming-is-depreca
https://stackoverflow.com/questions/19078325/naming-returned-columns-in-pandas-aggregate-function