如何分离这些明显链接的列？答案

【问题标题】：How do I separate these apparently linked columns?如何分离这些明显链接的列？
【发布时间】：2019-02-12 00:45:16
【问题描述】：

当我尝试使用 dplyr 的 select 命令来减少我拥有的列数时，遇到了一些奇怪的事情。我命名了三列，但我一直得到 4。除了星际迷航命令闪回链之外，我发现这种行为很奇怪，不知道如何解决它。另外，为什么会这样？

这是我的数据框，表示一天中每个时间段的出现次数。对于 6 行数据，它也非常冗长。

library(dplyr)
library(tidyr)
test <- structure(list(Day = c("Dec 10", "Dec 10", "Dec 10", "Dec 10", 
"Dec 11", "Dec 11"), Number = c(10L, 10L, 10L, 10L, 11L, 11L), 
    time = c("08:30", "12:00", "15:30", "19:00", "08:30", "12:00"
    ), Start = structure(c(1544430600, 1544443200, 1544455800, 
    1544468400, 1544517000, 1544529600), class = c("POSIXct", 
    "POSIXt"), tzone = "UTC"), n = c(29L, 74L, 20L, 26L, 29L, 
    32L)), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -6L), vars = c("Day", "Number", "time"), drop = TRUE, indices = list(
    0L, 1L, 2L, 3L, 4L, 5L), group_sizes = c(1L, 1L, 1L, 1L, 
1L, 1L), biggest_group_size = 1L, labels = structure(list(Day = c("Dec 10", 
"Dec 10", "Dec 10", "Dec 10", "Dec 11", "Dec 11"), Number = c(10L, 
10L, 10L, 10L, 11L, 11L), time = c("08:30", "12:00", "15:30", 
"19:00", "08:30", "12:00")), class = "data.frame", row.names = c(NA, 
-6L), vars = c("Day", "Number", "time"), drop = TRUE, indices = list(
    0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 
    14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 
    26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 
    38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 
    50L, 51L, 52L), group_sizes = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), biggest_group_size = 1L, labels = structure(list(
    Day = c("Dec 10", "Dec 10", "Dec 10", "Dec 10", "Dec 11", 
    "Dec 11", "Dec 11", "Dec 11", "Dec 12", "Dec 12", "Dec 12", 
    "Dec 12", "Dec 13", "Dec 13", "Dec 13", "Dec 13", "Dec 14", 
    "Dec 14", "Dec 14", "Dec 14", "Dec 15", "Dec 15", "Dec 15", 
    "Dec 17", "Dec 17", "Dec 17", "Dec 17", "Dec 18", "Dec 18", 
    "Dec 18", "Dec 18", "Dec 19", "Dec 19", "Dec 19", "Dec 4", 
    "Dec 4", "Dec 4", "Dec 4", "Dec 5", "Dec 5", "Dec 5", "Dec 5", 
    "Dec 6", "Dec 6", "Dec 6", "Dec 6", "Dec 7", "Dec 7", "Dec 7", 
    "Dec 7", "Dec 8", "Dec 8", "Dec 8"), Number = c(10L, 10L, 
    10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 13L, 13L, 
    13L, 13L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 17L, 17L, 17L, 
    17L, 18L, 18L, 18L, 18L, 19L, 19L, 19L, 4L, 4L, 4L, 4L, 5L, 
    5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L), 
    time = c("08:30", "12:00", "15:30", "19:00", "08:30", "12:00", 
    "15:30", "19:00", "08:30", "12:00", "15:30", "19:00", "08:30", 
    "12:00", "15:30", "19:00", "08:30", "12:00", "15:30", "19:00", 
    "08:30", "12:00", "15:30", "08:30", "12:00", "15:30", "19:00", 
    "08:30", "12:00", "15:30", "19:00", "08:30", "12:00", "15:30", 
    "08:30", "12:00", "15:30", "19:00", "08:30", "12:00", "15:30", 
    "19:00", "08:30", "12:00", "15:30", "19:00", "08:30", "12:00", 
    "15:30", "19:00", "08:30", "12:00", "15:30")), class = "data.frame", row.names = c(NA, 
-53L), vars = c("Day", "Number", "time"), drop = TRUE)))

您可以在输出中看到仅列出了 3 个变量，但奇怪的是显示了更多。当我选择特定变量或减去其他变量时，它将不起作用。

test %>% 
  select(Day, time, n)

【问题讨论】：

你的输出是什么？我得到四列：Number Day time n
请同时提及使用的库 (dplyr, tidyr)。
这也是我的输出@Nakx。不管我如何过滤。
stackoverflow.com/questions/38511743/…

标签： r dplyr

【解决方案1】：

在选择变量之前应取消分组，如"Adding missing grouping variables" message in dplyr in R 所述：

没有取消分组：

test %>% 
  select(Day, time, n)

> test %>% 
+   select(Day, time, n)
Adding missing grouping variables: `Number`
# A tibble: 6 x 4
# Groups:   Day, Number, time [6]
  Number Day    time      n
   <int> <chr>  <chr> <int>
1     10 Dec 10 08:30    29
2     10 Dec 10 12:00    74
3     10 Dec 10 15:30    20
4     10 Dec 10 19:00    26
5     11 Dec 11 08:30    29
6     11 Dec 11 12:00    32

取消分组

test %>% 
  ungroup() %>%
  select(Day, time, n)

> test %>% 
+   ungroup() %>%
+   select(Day, time, n)
# A tibble: 6 x 3
  Day    time      n
  <chr>  <chr> <int>
1 Dec 10 08:30    29
2 Dec 10 12:00    74
3 Dec 10 15:30    20
4 Dec 10 19:00    26
5 Dec 11 08:30    29
6 Dec 11 12:00    32

【讨论】：

【解决方案2】：

取消分组数据框可以解决所有问题。

【讨论】：