Closed hadley closed 4 years ago
if_else recode/plyr::revalue case_when plyr::mapvalues
vec_modify (list_modify) vec_merge
cut_interval cut_number cut_width
near between
trim prop
roll cum par row - is this still needed? or would just be row-vectorised? i.e. what does min(data.frame) return? or can it be parallel + splat?
lead lag
sample rep_along
interleave
row_number ntile min_rank dense_rank percent_rank cume_dist
obj_equal vec_equal obj_identical vec_identical
fill replace_na na_along
extract separate
first last nth
mode
vec_same == all(vec_equal(x, x[[1]]))
Transformation
Flexible
if_else recode/plyr::revalue case_when plyr::mapvalues
Combine
vec_modify (list_modify) vec_merge
Continuous -> discrete
cut_interval cut_number cut_width
Numeric
near between
trim prop
Families
roll cum par row - is this still needed? or would just be row-vectorised? i.e. what does min(data.frame) return? or can it be parallel + splat?
Position
lead lag
sample rep_along
interleave
Ranking
row_number ntile min_rank dense_rank percent_rank cume_dist
Equality
obj_equal vec_equal obj_identical vec_identical
Missing
fill replace_na na_along
String
extract separate
Summary
Position
first last nth
mode
Equality
vec_same == all(vec_equal(x, x[[1]]))