有人可以告诉我如何使用dplyr将带有参数名称的向量传递给函数吗?
library("dplyr", quietly = TRUE, warn.conflicts = FALSE) # version 0.8.0.1
# Does not work
iris %>% rowwise() %>% mutate(v1 = mean( as.name(names(iris)[-5]) ) )
iris %>% rowwise() %>% mutate(v1 = mean( !!(names(iris)[-5]) ) )
iris %>% rowwise() %>% mutate(v1 = mean( enquo(names(iris)[-5]) ) )
iris %>% rowwise() %>%
mutate(v1 = mean( c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width") ) )
# This works and is the intended result
iris %>% rowwise() %>%
mutate(v1 = mean( c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width ) ) )
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关键是要让函数(均值或任何函数)与names(iris)[-5]变量名称一起使用或使用向量。
我看这里没有成功: dplyr mutate_each_标准评估; dplyr:标准评估和enquo()
我的会议信息:
R version 3.5.3 (2019-03-11)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252
[3] LC_MONETARY=French_France.1252 LC_NUMERIC=C
[5] LC_TIME=French_France.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggplot2_3.1.0 visdat_0.5.3 lubridate_1.7.4 naniar_0.4.2
[5] dplyr_0.8.0.1
loaded via a namespace (and not attached):
[1] Rcpp_1.0.1 rstudioapi_0.10 magrittr_1.5 tidyselect_0.2.5
[5] munsell_0.5.0 colorspace_1.4-0 R6_2.4.0 rlang_0.3.4
[9] fansi_0.4.0 stringr_1.4.0 plyr_1.8.4 tools_3.5.3
[13] grid_3.5.3 packrat_0.5.0 gtable_0.2.0 utf8_1.1.4
[17] cli_1.1.0 withr_2.1.2 digest_0.6.18 lazyeval_0.2.2
[21] assertthat_0.2.0 tibble_2.1.1 crayon_1.3.4 tidyr_0.8.3
[25] purrr_0.3.2 glue_1.3.1 labeling_0.3 stringi_1.4.3
[29] compiler_3.5.3 pillar_1.3.1 scales_1.0.0 pkgconfig_2.0.2
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提前致谢 !
使用 map2_dbl
library(tidyverse)
iris %>% mutate(v1 = map2_dbl(Sepal.Length, Sepal.Width, ~mean(c(.x, .y)))) %>% head
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species v1
#1 5.1 3.5 1.4 0.2 setosa 4.30
#2 4.9 3.0 1.4 0.2 setosa 3.95
#3 4.7 3.2 1.3 0.2 setosa 3.95
#4 4.6 3.1 1.5 0.2 setosa 3.85
#5 5.0 3.6 1.4 0.2 setosa 4.30
#6 5.4 3.9 1.7 0.4 setosa 4.65
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或者,如果您想获取mean某些列。
cols <- c("Sepal.Length", "Sepal.Width")
iris %>% mutate(v1 = rowMeans(.[cols])) %>% head
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