我正在使用以下软件包版本
# devtools::install_github("hadley/dplyr")
> packageVersion("dplyr")
[1] ‘0.5.0.9001’下面是一个例子：
library(dplyr)
df <- structure(list(gene_symbol = structure(1:6, .Label = c("0610005C13Rik",
"0610007P14Rik", "0610009B22Rik", "0610009L18Rik", "0610009O20Rik",
"0610010B08Rik"), class = "factor"), fold_change = c(1.54037,
1.10976, 0.785, 0.79852, 0.91615, 0.87931), pvalue = c(0.5312,
0.00033, 0, 0.00011, 0.00387, 0.01455), ctr.mean_exp = c(0.00583,
59.67286, 83.2847, 6.88321, 14.67696, 1.10363), tre.mean_exp = c(0.00899,
66.22232, 65.37819, 5.49638, 13.4463, 0.97043), ctr.cv = c(5.49291,
0.20263, 0.17445, 0.46288, 0.2543, 0.39564), tre.cv = c(6.06505,
0.28827, 0.33958, 0.53295, 0.26679, 0.52364)), .Names = c("gene_symbol",
"fold_change", "pvalue", "ctr.mean_exp", "tre.mean_exp", "ctr.cv",
"tre.cv"), row.names = c(NA, -6L), class = c("tbl_df", "tbl",
"data.frame"))它看起来像这样：
> df
# A tibble: 6 × 7
gene_symbol fold_change pvalue ctr.mean_exp tre.mean_exp ctr.cv tre.cv
<fctr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 0610005C13Rik 1.54037 0.53120 0.00583 0.00899 5.49291 6.06505
2 0610007P14Rik 1.10976 0.00033 59.67286 66.22232 0.20263 0.28827
3 0610009B22Rik 0.78500 0.00000 83.28470 65.37819 0.17445 0.33958
4 0610009L18Rik 0.79852 0.00011 6.88321 5.49638 0.46288 0.53295
5 0610009O20Rik 0.91615 0.00387 14.67696 13.44630 0.25430 0.26679
6 0610010B08Rik 0.87931 0.01455 1.10363 0.97043 0.39564 0.52364我想四舍五入的浮动（第二列向前），以3位数。如何使用dplyr::mutate_all()
我试过这个：
cols <- names(df)[2:7]
# df <- df %>% mutate_each_(funs(round(.,3)), cols)
# Warning message:
#'mutate_each_' is deprecated.
# Use 'mutate_all' instead.
# See help("Deprecated")
df <- df %>% mutate_all(funs(round(.,3)), cols)但得到以下错误：
Error in mutate_impl(.data, dots) :
3 arguments passed to 'round'which requires 1 or 2 arguments
2条答案
按热度按时间bt1cpqcv1#
虽然新的
across()函数比以前的mutate_if变体稍微详细一些，但dplyr 1.0.0更新使tidyverse语言和代码更加一致和通用。这是如何舍入指定的列：
df %>% mutate(across(2:7, round, 3))#按位置排列的第2-7列df %>% mutate(across(cols, round, 3))#由变量cols指定的列以下是如何将所有数值列舍入到3位小数：
df %>% mutate(across(where(is.numeric), round, 3))这是如何舍入所有列，但它在这种情况下不起作用，因为gene_symbol不是数值：
df %>% mutate(across(everything(), round, 3))在我们将
where(is.numeric)放入across的参数中的地方，您可以放入其他列规范，如-1或-gene_symbol，以排除列1。请参阅help(tidyselect)以了解更多选项。更新为dafer 1.0.0
across()函数替换了dplyr动词的_if/_all/_at/_each变体。https://dplyr.tidyverse.org/dev/articles/colwise.html#how-do-you-convert-existing-code旧的答案：由于有些列不是数值型的，你可以使用
mutate_if，如果（当且仅当）它是数值型的，则可以对列进行舍入：df %>% mutate_if(is.numeric, round, 3)jogvjijk2#
尝试
It works！！