R转置包括NA

Question

我有像

这样的数据

trackingnumer = c(1,1,2,2,3) 
date = c("2017-08-01", "2017-08-10", "2017-08-02", "2017-08-05", "2017-08-12") 
scan = c("Pickup", "Delivered", "Pickup", "Delivered", "Delivered") 
df = data.frame(trackingnumer, date, scan) 

我想通过trackignumber转置此数据

df2 <- df %>% 
group_by(trackingnumer) %>% 
mutate(n = row_number()) %>% 
{data.table::dcast(data = setDT(.), trackingnumer ~ n, value.var = c('date', 'scan'))}

我尝试了这个，但是我无法获得理想的结果。我想将data_1设置为取件日期，将date_2设置为交付日期。如您所见，trackingnumber 3没有提取记录，所以我希望date_1为NA。

Answer 1

基准R尝试，使用relevel设置scan列的相应排序：

reshape(
  cbind(df, time=as.numeric(relevel(df$scan, "Pickup"))),
  idvar="trackingnumer", direction="wide", sep="_"
)

#  trackingnumer     date_1 scan_1     date_2    scan_2
#1             1 2017-08-01 Pickup 2017-08-10 Delivered
#3             2 2017-08-02 Pickup 2017-08-05 Delivered
#5             3       <NA>   <NA> 2017-08-12 Delivered

Answer 2

问题是你在mutate中的函数只计算行数，而不是注意它们中的内容。 case_when（）函数允许您根据“scan”的值为“n”列指定特定值

df2 <- df %>% 
  group_by(trackingnumer) %>% 
  mutate(n = case_when(scan == "Pickup" ~ 1,
                       scan == "Delivered" ~ 2)) %>% 
  {data.table::dcast(data = setDT(.), trackingnumer ~ n, value.var = c('date', 'scan'))}

Answer 3

或tidyr

library(tidyr)
df %>% group_by(trackingnumer,scan2 = scan) %>%
  nest(date,scan) %>%
  spread(scan2,data) %>%
  mutate_at(c("Delivered","Pickup"),~ifelse(map_lgl(.x,is_tibble),.x,lst(tibble(date=NA,scan=NA)))) %>%
  unnest %>%
  rename_at(c("date","scan"),paste0,2)

# # A tibble: 3 x 5
#     trackingnumer      date2     scan2      date1  scan1
#             <dbl>     <fctr>    <fctr>     <fctr> <fctr>
#   1             1 2017-08-10 Delivered 2017-08-01 Pickup
#   2             2 2017-08-05 Delivered 2017-08-02 Pickup
#   3             3 2017-08-12 Delivered       <NA>   <NA>