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我想在其中使用该across()功能，dplyr但出现错误。例如，运行

iris %>%
  group_by(Species) %>%
  summarise(across(starts_with("Sepal"), mean))

给我

Error in across(starts_with("Sepal"), mean) : 
  could not find function "across"

across()是最近的介绍https://towardsdatascience.com/what-you-need-to-know-about-the-new-dplyr-1-0-0-7eaaaf6d78ac in dplyr。但是，包dplyr已更新并加载

packageVersion('dplyr')
[1] ‘1.0.0’

检查内部dplyr

ls("package:dplyr")
  [1] "%>%"                   "add_count"             "add_count_"            "add_row"               "add_rownames"          "add_tally"            
  [7] "add_tally_"            "all_equal"             "all_vars"              "anti_join"             "any_vars"              "arrange"              
 [13] "arrange_"              "arrange_all"           "arrange_at"            "arrange_if"            "as_data_frame"         "as_label"

我发现它across不存在，但是如果我在帮助程序中查找该功能，?across我会得到解释across.

怎么去across上班？

- - - 编辑 - - -

我sessionInfo()的如下：

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] tidyselect_1.1.0 dplyr_1.0.0     

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3       cellranger_1.1.0 pillar_1.4.2     compiler_3.6.1   forcats_0.4.0    tools_3.6.1      jsonlite_1.6     lubridate_1.7.4  lifecycle_0.2.0 
[10] tibble_2.1.3     nlme_3.1-140     gtable_0.3.0     lattice_0.20-38  pkgconfig_2.0.3  rlang_0.4.6      cli_1.1.0        rstudioapi_0.10  haven_2.1.1     
[19] xml2_1.2.2       httr_1.4.1       stringr_1.4.0    generics_0.0.2   vctrs_0.3.1      hms_0.5.1        grid_3.6.1       glue_1.4.1       R6_2.4.0        
[28] fansi_0.4.0      readxl_1.3.1     readr_1.3.1      modelr_0.1.5     tidyr_1.0.0      purrr_0.3.3      ggplot2_3.2.1    magrittr_1.5     backports_1.1.4 
[37] scales_1.0.0     rvest_0.3.4      assertthat_0.2.1 tidyverse_1.2.1  colorspace_1.4-1 utf8_1.1.4       stringi_1.4.3    lazyeval_0.2.2   munsell_0.5.0   
[46] broom_0.5.2      crayon_1.3.4    
> .libPaths()
[1] "/Library/Frameworks/R.framework/Versions/3.6/Resources/library"
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1 回答 1

2

cross 函数仅在 dplyr 的开发版本中可用，在尚未使用 accross 函数的 CRAN 上可用，请使用以下代码安装 dplyr dev 版本

install.packages("devtools")

library(devtools)
devtools::install_github("tidyverse/dplyr")
library(dplyr)

现在你的代码应该可以工作了

data("iris")
iris %>%
  group_by(Species) %>%
  summarise(across(starts_with("Sepal"), mean))

输出

# A tibble: 3 x 3
  Species    Sepal.Length Sepal.Width
  <fct>             <dbl>       <dbl>
1 setosa             5.01        3.43
2 versicolor         5.94        2.77
3 virginica          6.59        2.97
于 2021-05-18T07:52:13.280 回答