子集后数据不再是数字

Question

我正试图根据下面数据集中的TMtClones列来子集一个数据集。我想只为TmTClones desiree子集YldAll。然而，当我尝试子集时，结果数据不再是数字。我的数据如下。

structure(list(Year = c(2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018), Location = c("Khangma", 
"Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
"Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
"Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
"Khangma", "Khangma", "Khangma", "Khangma", "Khangma"), TmtClones = 
c("304357.31", 
"306518.1", "306519.64", "399004.19", "399078.11", "395436.8", 
"397196.3", "Desiree", "304357.31", "306518.1", "306519.64", 
"399004.19", "399078.11", "395436.8", "397196.3", "Desiree", 
"304357.31", "306518.1", "306519.64", "399004.19", "399078.11", 
"395436.8", "397196.3", "Desiree"), YldAll = c(10.3, 10.9, 8.5, 
10.2, 9.5, 6.8, 4.8, 8.5, 10.9, 8.7, 9.7, 12, 10.3, 5.3, 5.7, 
8.2, 10.9, 11.9, 4, 10.2, 5, 4.7, 2.5, 7.9)), row.names = c(NA, 
-24L), class = c("tbl_df", "tbl", "data.frame"))

我尝试用两种不同的方式进行子集，如下面的代码所示。

YldAll.Desiree <- subset(potato.data2, TmtClones == "Desiree", select 
= YldAll)

YldAll.Desiree2 <- potato.data2 %>%
  filter(TmtClones == "Desiree") %>%
  select(YldAll)

在这两种情况下，根据is.numeric()，产生的数据都不再是数字型的，当我试图使用它时，我得到了错误。我想不通为什么，因为is.numeric(pato.data2$YldAll)给出了TRUE。如果我试图将YldAll.Desiree或YldAll.Desiree2胁迫为数值型，我得到了错误--'list'对象不能被胁迫为'double'类型。

Answer 1

data.frame不能是数字，因为它是一个列表。而矩阵可以是二维数字对象。当你调用 is.numeric/as.numeric 它应该在 data.frame 而不是全部 data.frame. 见例：

potato.data2 <- structure(
  list(
    Year = c(2018, 2018, 2018, 2018, 2018, 2018, 2018, 
             2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
             2018, 2018, 2018, 2018, 2018, 2018), 
    Location = c("Khangma", 
                 "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
                 "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
                 "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", "Khangma", 
                 "Khangma", "Khangma", "Khangma", "Khangma", "Khangma"), 
    TmtClones = 
      c("304357.31", 
        "306518.1", "306519.64", "399004.19", "399078.11", "395436.8", 
        "397196.3", "Desiree", "304357.31", "306518.1", "306519.64", 
        "399004.19", "399078.11", "395436.8", "397196.3", "Desiree", 
        "304357.31", "306518.1", "306519.64", "399004.19", "399078.11", 
        "395436.8", "397196.3", "Desiree"), 
    YldAll = c(10.3, 10.9, 8.5, 
               10.2, 9.5, 6.8, 4.8, 8.5, 10.9, 8.7, 9.7, 12, 10.3, 5.3, 5.7, 
               8.2, 10.9, 11.9, 4, 10.2, 5, 4.7, 2.5, 7.9)), 
  row.names = c(NA, -24L), 
  class = c("tbl_df", "tbl", "data.frame")
)
str(potato.data2)
#> Classes 'tbl_df', 'tbl' and 'data.frame':    24 obs. of  4 variables:
#>  $ Year     : num  2018 2018 2018 2018 2018 ...
#>  $ Location : chr  "Khangma" "Khangma" "Khangma" "Khangma" ...
#>  $ TmtClones: chr  "304357.31" "306518.1" "306519.64" "399004.19" ...
#>  $ YldAll   : num  10.3 10.9 8.5 10.2 9.5 6.8 4.8 8.5 10.9 8.7 ...
is.numeric(potato.data2)
#> [1] FALSE
is.numeric(potato.data2$YldAll)
#> [1] TRUE


library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
YldAll.Desiree2 <- potato.data2 %>%
  filter(TmtClones == "Desiree") %>%
  select(YldAll)
str(YldAll.Desiree2)
#> tibble [3 x 1] (S3: tbl_df/tbl/data.frame)
#>  $ YldAll: num [1:3] 8.5 8.2 7.9
is.numeric(YldAll.Desiree2)
#> [1] FALSE
is.numeric(YldAll.Desiree2$YldAll)
#> [1] TRUE