在Y列数据的情况下对X列数据进行转置

library(dplyr)
library(tidyr)

df = read.table(text = "
ROW   date      names
1     1.1.2000  A
2     NA        B
3     NA        C
4     1.1.2000  X
5     NA        Y
6     2.1.2000  Z
", header=T, stringsAsFactors=F)

df %>%
  group_by(ROW = cumsum(!is.na(date))) %>%       # create the rows of updated dataset based on rows without NAs; for each new row:
  mutate(counter = row_number(),                 # count how many columns you need for each new row
         date = unique(date[!is.na(date)])) %>%  # keep unique date after excluding NAs
  ungroup() %>%                                  # forget the grouping
  mutate(counter = paste0("name",counter)) %>%   # update variable to use as column names
  spread(counter, names)                         # reshape dataset

# # A tibble: 3 x 5
#     ROW     date name1 name2 name3
# * <int>    <chr> <chr> <chr> <chr>
# 1     1 1.1.2000     A     B     C
# 2     2 1.1.2000     X     Y  <NA>
# 3     3 2.1.2000     Z  <NA>  <NA>