R: Gather/Spread/Reshape 21 Columns Based on 21 Other Column s

Question

我想根据某些字段中的值创建列，并由其他字段中的值填充。例如 column1_time 的值为“1030”，column1_status 的值为 "booked"。我想将它们转换到一个新字段 time1030 中，值为 "booked." 有 21 个带有时间的唯一列（时间每行只列出一次，因此它们在 21 列中是唯一的）——并且有21 个独特的列，其状态映射回时间列。因此，这 42 个时间+状态列应重新排列为每个唯一时间的一列，并由该时间的相应状态填充。

我有这样的数据：

我想利用 R 的 gather/spread 或 reshape2（遗留）功能将此数据转置为如下所示：

我研究了 gather 和 spread 几个小时，但还是想不出来。我认为将键设置为 ends_with('_time') 并将值设置为 ends_with('_status') 可能会起作用，但我的尝试并没有起作用。

对于可重现的数据示例：

structure(list(appointment1_time = c("1030", "1030"), appointment2_time = c("1100", 
"1100"), appointment3_time = c("1130", "1130"), appointment4_time = c("1200", 
"1200"), appointment5_time = c("1230", "1230"), appointment6_time = c("0100", 
"0100"), appointment7_time = c("0130", "0130"), appointment8_time = c("0200", 
"0200"), appointment9_time = c("0230", "0230"), appointment10_time = c("0300", 
"0300"), appointment11_time = c("0330", "0330"), appointment12_time = c("0400", 
"0400"), appointment13_time = c("0430", "0430"), appointment14_time = c("0500", 
"0500"), appointment15_time = c("0530", "0530"), appointment16_time = c("0600", 
""), appointment17_time = c("0630", ""), appointment18_time = c("0700", 
""), appointment19_time = c("0730", ""), appointment20_time = c(NA_character_, 
NA_character_), appointment21_time = c(NA_character_, NA_character_
), appointment1_status = c("booked", "available"), appointment2_status = c("booked", 
"available"), appointment3_status = c("booked", "available"), 
    appointment4_status = c("booked", "available"), appointment5_status = c("booked", 
    "available"), appointment6_status = c("booked", "available"
    ), appointment7_status = c("booked", "available"), appointment8_status = c("booked", 
    "available"), appointment9_status = c("booked", "available"
    ), appointment10_status = c("booked", "available"), appointment11_status = c("booked", 
    "available"), appointment12_status = c("available", "available"
    ), appointment13_status = c("available", "available"), appointment14_status = c("available", 
    "available"), appointment15_status = c("booked", "available"
    ), appointment16_status = c("available", ""), appointment17_status = c("available", 
    ""), appointment18_status = c("available", ""), appointment19_status = c("available", 
    ""), appointment20_status = c(NA_character_, NA_character_
    ), appointment21_status = c(NA_character_, NA_character_)), row.names = 1:2, class = "data.frame")

Answer 1

使用 tidyverse 的解决方案。

library(tidyverse)

# Get the time order
ord <- dat %>% select(ends_with("time")) %>% slice(1) %>% unlist()
# Remove NA
ord <- ord[!is.na(ord)]

dat2 <- dat %>%
  rowid_to_column() %>%
  gather(Column, Value, -rowid) %>%
  separate(Column, into = c("Apt", "time/status"), sep = "_") %>%
  spread(`time/status`, Value) %>%
  # Remove NA or "" in the status column
  filter(!is.na(status) & !status %in% "") %>%
  mutate(Apt = str_c("apt_slot", time, sep = "_")) %>%
  select(-time) %>%
  spread(Apt, status) %>%
  select(-rowid) %>%
  # Reorder the column
  select(str_c("apt_slot", ord, sep = "_"))

dat2
# apt_slot_1030 apt_slot_1100 apt_slot_1130 apt_slot_1200 apt_slot_1230 apt_slot_0100 apt_slot_0130
# 1        booked        booked        booked        booked        booked        booked        booked
# 2     available     available     available     available     available     available     available
# apt_slot_0200 apt_slot_0230 apt_slot_0300 apt_slot_0330 apt_slot_0400 apt_slot_0430 apt_slot_0500
# 1        booked        booked        booked        booked     available     available     available
# 2     available     available     available     available     available     available     available
# apt_slot_0530 apt_slot_0600 apt_slot_0630 apt_slot_0700 apt_slot_0730
# 1        booked     available     available     available     available
# 2     available          <NA>          <NA>          <NA>          <NA>

R: Gather/Spread/Reshape 21 Columns Based on 21 Other Column s

R: Gather/Spread/Reshape 21 Columns Based on 21 Other Column s

transpose

r

spread

reshape2

tidyr