将行名转换为第一列 [英] Convert row names into first column

问题描述

我有一个这样的数据框架：

I have a data frame like this:

df
             VALUE              ABS_CALL DETECTION P-VALUE    
    1007_s_at "957.729231881542" "P"      "0.00486279317241156"
    1053_at   "320.632701283368" "P"      "0.0313356324173416" 
    117_at    "429.842323161046" "P"      "0.0170004527476119" 
    121_at    "2395.7364289242"  "P"      "0.0114473584876183" 
    1255_g_at "116.493632746934" "A"      "0.39799368200131"   
    1294_at   "739.927122116896" "A"      "0.0668649772942343" 

我想将行名转换为第一列。目前我使用这样的方式使行名作为第一列：

I want to convert the row names into the first column. Currently I use something like this to make row names as the first column:

  d <- df
  names <- rownames(d)
  rownames(d) <- NULL
  data <- cbind(names,d)

有没有一行这样做？

推荐答案

你可以通过引用删除行名称并将其转换为列（使用 - > 不使用<$ c $重新分配内存） c> setDT 及其 keep.rownames = TRUE 参数从 data.table

You can both remove row names and convert them to a column by reference (without reallocating memory using ->) using setDT and its keep.rownames = TRUE argument from the data.table package

library(data.table)
setDT(df, keep.rownames = TRUE)[]
#    rn     VALUE  ABS_CALL DETECTION     P.VALUE
# 1:  1 1007_s_at  957.7292         P 0.004862793
# 2:  2   1053_at  320.6327         P 0.031335632
# 3:  3    117_at  429.8423         P 0.017000453
# 4:  4    121_at 2395.7364         P 0.011447358
# 5:  5 1255_g_at  116.4936         A 0.397993682
# 6:  6   1294_at  739.9271         A 0.066864977

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