R 生成一个字符变量作为ID变量
我有以下结构的数据框：R 生成一个字符变量作为ID变量,r,string,R,String,我有以下结构的数据框： structure(list(DateTime = structure(c(1578009600, 1578096000, 1578182400, 1578268800, 1578268800, 1578441600, 1578528000, 1578700800, 1578873600, 1578960000, 1579046400, 1579219200, 1579305600, 1579651200, 1579737600, 1579910400, 15799
structure(list(DateTime = structure(c(1578009600, 1578096000,
1578182400, 1578268800, 1578268800, 1578441600, 1578528000, 1578700800,
1578873600, 1578960000, 1579046400, 1579219200, 1579305600, 1579651200,
1579737600, 1579910400, 1579996800, 1580083200, 1580256000, 1580342400
), class = c("POSIXct", "POSIXt"), tzone = "UTC"), Y = c(0.398128487169134,
0.943205112163668, 0.28252751156162, 0.249960153693576, 0.795387767024049,
0.944143005087556, 0.158092709898581, 0.0939977195370584, 0.363535430584373,
0.44838029451066, 0.693205040632161, 0.552676175195101, 0.985732436206492,
0.496368199684004, 0.534787647236829, 0.327063363194893, 0.790654871992939,
0.568471157855241, 0.837558574291766, 0.643802685572038), Var1 = c(0,
0, 0, 0, 0, 0, 0.94290146, 0, 0, 0, 0, 0, 0, 0, 0.684747396078389,
0, 0, 0, 0, 0), Var2 = c(0, 0.554797180422304, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Var3 = c(0, 0, 0, 0.815909158957364,
0, 0, 0, 0, 0, 0.648069655007399, 0, 0.501910457604968, 0, 0,
0, 0, 0, 0.356728763364177, 0, 0), ID = c("0", "Var2", "0", "Var3",
"0", "0", "0", "0", "0", "Var3", "0", "Var3", "0", "0", "0",
"0", "0", "Var3", "0", "0")), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
ID1Var1Var2Var3ID2IDID2#1 DateTime Y Var1 Var2 Var3
#2 3/1/20 0.67 0.00 0.00 0.00
#3 4/1/20 0.31 0.00 0.11 0.00
#4 5/1/20 0.96 0.00 0.00 0.00
#5 6/1/20 0.28 0.00 0.00 0.40
#6 6/1/20 0.28 0.00 0.00 0.00
#7 8/1/20 0.48 0.00 0.00 0.00
#8 9/1/20 0.07 0.94 0.00 0.00
#9 11/1/20 0.94 0.00 0.00 0.00
#10 13/1/20 0.05 0.00 0.00 0.00
#11 14/1/20 0.04 0.00 0.00 0.53
#12 15/1/20 0.93 0.00 0.00 0.00
#13 17/1/20 0.30 0.00 0.00 0.32
#14 18/1/20 0.75 0.00 0.00 0.00
#15 22/1/20 0.99 0.00 0.00 0.00
#16 23/1/20 0.32 0.15 0.00 0.00
#17 25/1/20 0.51 0.00 0.00 0.00
#18 26/1/20 0.15 0.00 0.00 0.00
#19 27/1/20 0.78 0.00 0.00 0.15
#20 29/1/20 0.83 0.00 0.00 0.00
#21 30/1/20 0.10 0.00 0.00 0.00
IDID2d$ID <- NULL # dropping this column, as we need to re-create it.
ix <- which(d[, 3:5] != 0, arr.ind = TRUE)
d[ ix[ , 1], "ID"] <- colnames(d[, 3:5])[ ix[, 2] ]
d$ID2 <- as.numeric(as.factor(d$ID))
d
## A tibble: 20 x 7
# DateTime Y Var1 Var2 Var3 ID ID2
# <dttm> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
# 1 2020-01-03 00:00:00 0.398 0 0 0 NA NA
# 2 2020-01-04 00:00:00 0.943 0 0.555 0 Var2 2
# 3 2020-01-05 00:00:00 0.283 0 0 0 NA NA
# 4 2020-01-06 00:00:00 0.250 0 0 0.816 Var3 3
# 5 2020-01-06 00:00:00 0.795 0 0 0 NA NA
# 6 2020-01-08 00:00:00 0.944 0 0 0 NA NA
# 7 2020-01-09 00:00:00 0.158 0.943 0 0 Var1 1
# 8 2020-01-11 00:00:00 0.0940 0 0 0 NA NA
# 9 2020-01-13 00:00:00 0.364 0 0 0 NA NA
# 10 2020-01-14 00:00:00 0.448 0 0 0.648 Var3 3
# 11 2020-01-15 00:00:00 0.693 0 0 0 NA NA
# 12 2020-01-17 00:00:00 0.553 0 0 0.502 Var3 3
# 13 2020-01-18 00:00:00 0.986 0 0 0 NA NA
# 14 2020-01-22 00:00:00 0.496 0 0 0 NA NA
# 15 2020-01-23 00:00:00 0.535 0.685 0 0 Var1 1
# 16 2020-01-25 00:00:00 0.327 0 0 0 NA NA
# 17 2020-01-26 00:00:00 0.791 0 0 0 NA NA
# 18 2020-01-27 00:00:00 0.568 0 0 0.357 Var3 3
# 19 2020-01-29 00:00:00 0.838 0 0 0 NA NA
# 20 2020-01-30 00:00:00 0.644 0 0 0 NA NA
d$IDdf%>%
突变（ID=select（，Var1:Var3）%>%
{ifelse（行和（.）！=0，名称（.）[max.col（.）]，0）}，
ID2=as.integer（有序（ID，唯一（ID））-1）
日期时间Y Var1 Var2 Var3 ID ID2
1 2020-01-03 00:00:00 0.398 0 0 0 0 0
2020-01-04 00:00:00 0.943 0.555 0 Var2 1
3 2020-01-05 00:00:00 0.283 0 0 0 0 0
4 2020-01-06 00:00:00 0.250 0.816 Var3 2
5 2020-01-06 00:00:00 0.795 0 0 0 0 0
6 2020-01-08 00:00:00 0.944 0 0 0 0 0
7 2020-01-09 00:00:00 0.158 0.943 0 Var1 3
8 2020-01-11 00:00:00 0.0940 0 0 0 0 0
9 2020-01-13 00:00:00 0.364 0 0 0 0 0
10 2020-01-14 00:00:00 0.4480 0 0.648 Var3 2
11 2020-01-15 00:00:00 0.693 0 0 0 0 0
12 2020-01-17 00:00:00 0.553 0 0.502 Var3 2
13 2020-01-18 00:00:00 0.986 0 0 0 0 0
14 2020-01-22 00:00:00 0.496 0 0 0 0 0
15 2020-01-23 00:00:00 0.535 0.685 0 Var1 3
16 2020-01-25 00:00:00 0.327 0 0 0 0 0
17 2020-01-26 00:00:00 0.791 0 0 0 0 0
18 2020-01-27 00:00:00 0.5680 0.357 Var3 2
19 2020-01-29 00:00:00 0.838 0 0 0 0 0
20 2020-01-30 00:00:00 0.644 0 0 0 0 0
为免生疑问，您能否给出前几个案例的预期输出？您是否也可以提供可用格式的数据：即作为数据框对象或使用dupt（…您的数据…）
Hi-Peter。谢谢你指出这一点。我一直想知道如何制作一个可复制的示例-您对dupt（…您的数据…
函数的引用帮助我解决了这个问题。我现在编辑了我的问题。我希望此编辑足以让您提取数据集。我认为有一个预期输出的示例会很有帮助。我认为您的dput（）
缺少变量ID2？您希望新变量看起来如何-ID和ID2部分之间有一个空格？感谢您提出答案，Onyanbu。将代码应用于数据帧时，我遇到以下错误：“select（，Var1:Var3）中的错误：未使用的参数（Var1:Var3）”
@CecSK Var1:Var3是变量Var1、var2、Var3
d$ID <- NULL # dropping this column, as we need to re-create it.
ix <- which(d[, 3:5] != 0, arr.ind = TRUE)
d[ ix[ , 1], "ID"] <- colnames(d[, 3:5])[ ix[, 2] ]
d$ID2 <- as.numeric(as.factor(d$ID))
d
## A tibble: 20 x 7
# DateTime Y Var1 Var2 Var3 ID ID2
# <dttm> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
# 1 2020-01-03 00:00:00 0.398 0 0 0 NA NA
# 2 2020-01-04 00:00:00 0.943 0 0.555 0 Var2 2
# 3 2020-01-05 00:00:00 0.283 0 0 0 NA NA
# 4 2020-01-06 00:00:00 0.250 0 0 0.816 Var3 3
# 5 2020-01-06 00:00:00 0.795 0 0 0 NA NA
# 6 2020-01-08 00:00:00 0.944 0 0 0 NA NA
# 7 2020-01-09 00:00:00 0.158 0.943 0 0 Var1 1
# 8 2020-01-11 00:00:00 0.0940 0 0 0 NA NA
# 9 2020-01-13 00:00:00 0.364 0 0 0 NA NA
# 10 2020-01-14 00:00:00 0.448 0 0 0.648 Var3 3
# 11 2020-01-15 00:00:00 0.693 0 0 0 NA NA
# 12 2020-01-17 00:00:00 0.553 0 0 0.502 Var3 3
# 13 2020-01-18 00:00:00 0.986 0 0 0 NA NA
# 14 2020-01-22 00:00:00 0.496 0 0 0 NA NA
# 15 2020-01-23 00:00:00 0.535 0.685 0 0 Var1 1
# 16 2020-01-25 00:00:00 0.327 0 0 0 NA NA
# 17 2020-01-26 00:00:00 0.791 0 0 0 NA NA
# 18 2020-01-27 00:00:00 0.568 0 0 0.357 Var3 3
# 19 2020-01-29 00:00:00 0.838 0 0 0 NA NA
# 20 2020-01-30 00:00:00 0.644 0 0 0 NA NA
df %>%
mutate(ID = select(., Var1:Var3) %>%
{ ifelse(rowSums(.) != 0, names(.)[max.col(.)], 0)},
ID2 = as.integer(ordered(ID,unique(ID))) - 1)
DateTime Y Var1 Var2 Var3 ID ID2
<dttm> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
1 2020-01-03 00:00:00 0.398 0 0 0 0 0
2 2020-01-04 00:00:00 0.943 0 0.555 0 Var2 1
3 2020-01-05 00:00:00 0.283 0 0 0 0 0
4 2020-01-06 00:00:00 0.250 0 0 0.816 Var3 2
5 2020-01-06 00:00:00 0.795 0 0 0 0 0
6 2020-01-08 00:00:00 0.944 0 0 0 0 0
7 2020-01-09 00:00:00 0.158 0.943 0 0 Var1 3
8 2020-01-11 00:00:00 0.0940 0 0 0 0 0
9 2020-01-13 00:00:00 0.364 0 0 0 0 0
10 2020-01-14 00:00:00 0.448 0 0 0.648 Var3 2
11 2020-01-15 00:00:00 0.693 0 0 0 0 0
12 2020-01-17 00:00:00 0.553 0 0 0.502 Var3 2
13 2020-01-18 00:00:00 0.986 0 0 0 0 0
14 2020-01-22 00:00:00 0.496 0 0 0 0 0
15 2020-01-23 00:00:00 0.535 0.685 0 0 Var1 3
16 2020-01-25 00:00:00 0.327 0 0 0 0 0
17 2020-01-26 00:00:00 0.791 0 0 0 0 0
18 2020-01-27 00:00:00 0.568 0 0 0.357 Var3 2
19 2020-01-29 00:00:00 0.838 0 0 0 0 0
20 2020-01-30 00:00:00 0.644 0 0 0 0 0