Transform a list of elements with similar structure into a list of decoupled fields
1 2 
.data 
A 
.fields 

... 
The custom aggregate functions. Can be a named list of functions or
character vectors. If a function is specified as a list of functions, then the
functions will be evaluated recursively on the result of the field. Use 
.aggregate 
The default aggregate function, by default, 
.missing 
When 
list.zip
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3)))
list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)))
list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'union')
list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'union', a = 'identity')
list.unzip(list(p1 = list(a = 1, b = 2), p2 = list(a = 2, b = 3, c = 4)), 'intersect', a = NULL)
x <
list(april = list(n_days = 30,
holidays = list(list('20150401', 'april fools'),
list('20150405', 'easter')),
month_info = c(number = '4', season = 'spring')),
july = list(n_days = 31,
holidays = list(list('20140704', 'july 4th')),
month_info = c(number = '7', season = 'summer')))
list.unzip(x, holidays = c('list.ungroup', 'unname', 'list.stack',
function(df) setNames(df, c("date", "name"))))

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