我的问题是这个。我有一个包含四列的数据框，名为CSES。我有一个名为meta的单独数据框，其中包含两列code和name。如果任何CSES列中的值都与meta$code相匹配，我想将其替换为meta$name中的值。
目前，我的解决方案使用循环，效果很好；但是有没有更好的方法来避免循环，最好使用Tidyverse？似乎是一个非常标准的问题，应该已经有了答案，但我没有找到任何答案。感谢您的帮助。干杯。
for(i in seq_along(meta$code)) {
code <- meta$code[[i]]
for(k in seq_along(CSES)) {
col <- CSES[[k]]
col[col == code] <- meta$name[[i]]
CSES[[k]] <- col
}
}
编辑：我在下面添加了输入数据和所需的输出，并阐明了每个请求的所需输出。
为澄清起见，期望如果meta$code列与CSES中的值匹配，则CSES中的值应更改为同一行上的meta$name值作为匹配的meta$code。
CSES，这是我要重新编码的数据：
# A tibble: 274,719 x 6
# IMD5000_A IMD5000_B IMD5000_C IMD5000_D IMD5000_E IMD5000_F
# <chr> <chr> <chr> <chr> <chr> <chr>
# 1 320001 320002 320003 320004 320005 320006
# 2 320001 320002 320003 320004 320005 320006
# 3 320001 320002 320003 320004 320005 320006
# 4 320001 320002 320003 320004 320005 320006
# 5 320001 320002 320003 320004 320005 320006
# 6 320001 320002 320003 320004 320005 320006
# 7 320001 320002 320003 320004 320005 320006
# 8 320001 320002 320003 320004 320005 320006
# 9 320001 320002 320003 320004 320005 320006
# 10 320001 320002 320003 320004 320005 320006
# … with 274,709 more rows
元：
# A tibble: 44 x 2
# code name
# <chr> <chr>
# 1 7520001 SAP
# 2 7520002 M
# 3 7520003 FP
# 4 7520004 KD
# 5 7520005 MP
# 6 7520006 C
# 7 7520007 V
# 8 7520008 SD
# 9 7520009 Fi
#10 7520010 Jl
# … with 34 more rows
例如，CSES中的值7520001应该更改为“ SAP”。
答案 0 :(得分：0)
示例数据：
set.seed(10)
CSES <- as.data.frame(matrix(sample(letters[1:10], 40, T), 10),
stringsAsFactors = F)
meta <- data.frame(code = letters[1:3], name = c('peach', 'pear', 'apple'),
stringsAsFactors = F)
CSES
# V1 V2 V3 V4
# 1 f g i f
# 2 d f g a
# 3 e b h b
# 4 g f d i
# 5 a d e e
# 6 c e h h
# 7 c a i i
# 8 c c c j
# 9 g d h g
# 10 e i d f
meta
# code name
# 1 a peach
# 2 b pear
# 3 c apple
现在使用与给定代码相对应的元名称来更新CSES的每一列
基数R
repl <- matrix(meta$name[match(as.matrix(CSES), meta$code)], nrow(CSES))
CSES[!is.na(repl)] <- repl[!is.na(repl)]
CSES
# V1 V2 V3 V4
# 1 f g i f
# 2 d f g peach
# 3 e pear h pear
# 4 g f d i
# 5 peach d e e
# 6 apple e h h
# 7 apple peach i i
# 8 apple apple apple j
# 9 g d h g
# 10 e i d f
dplyr
library(dplyr)
CSES %>%
mutate_all(~ coalesce(meta$name[match(.x, meta$code)], .x))
# V1 V2 V3 V4
# 1 f g i f
# 2 d f g peach
# 3 e pear h pear
# 4 g f d i
# 5 peach d e e
# 6 apple e h h
# 7 apple peach i i
# 8 apple apple apple j
# 9 g d h g
# 10 e i d f
data.table
library(data.table)
setDT(CSES)
setDT(meta)
for(n in names(CSES))
CSES[meta, on = setNames('code', n), (n) := i.name]
CSES[]
# V1 V2 V3 V4
# 1: f g i f
# 2: d f g peach
# 3: e pear h pear
# 4: g f d i
# 5: peach d e e
# 6: apple e h h
# 7: apple peach i i
# 8: apple apple apple j
# 9: g d h g
# 10: e i d f
答案 1 :(得分：0)
或者在基数R中，如果您将数据帧转换为因子，则可以重置级别来巧妙地执行此操作，或者可能更有效。
Name: some-ingress
Namespace: default
Address:
Default backend: default-http-backend:80 (<none>)
Rules:
Host Path Backends
---- ---- --------
*
/ ssl-redirect-default:use-annotation (<none>)
/* ssl-redirect:use-annotation (<none>)
/* some-service:80 (192.168.92.252:8080)
Annotations:
alb.ingress.kubernetes.io/actions.ssl-redirect: {"Type": "redirect", "RedirectConfig": { "Protocol": "HTTPS", "Port": "443", "StatusCode": "HTTP_301"}}
alb.ingress.kubernetes.io/actions.ssl-redirect-default: {"Type": "redirect", "RedirectConfig": { "Protocol": "HTTPS", "Path": "/someapp/#{path}", "Port": "443", "StatusCode": "HTTP_301"}}
alb.ingress.kubernetes.io/certificate-arn: arn:aws:acm:eu-central-1:...
alb.ingress.kubernetes.io/listen-ports: [{"HTTP": 80}, {"HTTPS":443}]
alb.ingress.kubernetes.io/scheme: internet-facing
kubernetes.io/ingress.class: alb
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal CREATE 16m alb-ingress-controller LoadBalancer some-alb created, ARN: some-alb-arn:loadbalancer/app/some-alb/some-ids
Normal CREATE 16m (x2 over 16m) alb-ingress-controller rule 1 created with conditions [{ Field: "path-pattern", Values: ["/"] }]
Normal CREATE 16m (x2 over 16m) alb-ingress-controller rule 2 created with conditions [{ Field: "path-pattern", Values: ["/*"] }]
Normal CREATE 16m alb-ingress-controller rule 3 created with conditions [{ Field: "path-pattern", Values: ["/*"] }]
带输出 [1]“ --- b
meta = data.frame(code=c('a','c'), name=c('A', 'C'), stringsAsFactors = F)
CSES = data.frame(code = c('a', 'b', 'c', 'd'), c2 = c(1,2,3,4), stringsAsFactors = F)
print("---before----")
print(CSES)
f <- CSES$code %in% meta$code
CSES$code[f] <- sapply(CSES$code[f], function(x) meta$name[which(x==meta$code)])
print("---after using factors and levels----")
print(CSES)
使用因素如下
efore----"
code c2
1 a 1
2 b 2
3 c 3
4 d 4
[1] "---after using factors and levels----"
code c2
1 A 1
2 b 2
3 C 3
4 d 4
有输出
meta2 = data.frame(code=c('a','c'), name=c('A', 'C'))
CSES2 = data.frame(code = c('a', 'b', 'c', 'd'), c2 = c(1,2,3,4))
frepl <- function(s){
if (s %in% meta2$code){levels(meta2$name)[meta2$code == s]} else {s}
}
levels(CSES2$code) <- sapply(levels(CSES2$code), function(s) frepl(s))
print("---after using factors and levels----")
print(CSES2)