英文:
Recoding continuous variable
问题
我有一个连续变量。条目1-60需要保持不变。NAs和0被编码为大于60的数字。
英文:
I have a continuous variable. Entries 1-60 need to stay the same. NAs and 0s are coded as a number above 60.
答案1
得分: 2
使用 `dplyr`，你可以使用
- `recode()`
```r
df %>%
mutate(y = recode(x, `88` = 0, `99` = NA_real_))
case_match()
df %>%
mutate(y = case_match(x, 88 ~ 0, 99 ~ NA, .default = x))
case_when()
df %>%
mutate(y = case_when(x == 88 ~ 0, x == 99 ~ NA, .default = x))
<details>
<summary>英文:</summary>
With `dplyr`, you can use
- `recode()`
```r
df %>%
mutate(y = recode(x, `88` = 0, `99` = NA_real_))
case_match()
df %>%
mutate(y = case_match(x, 88 ~ 0, 99 ~ NA, .default = x))
case_when()
df %>%
mutate(y = case_when(x == 88 ~ 0, x == 99 ~ NA, .default = x))
答案2
得分: 1
使用 `fcase`
库(data.table)
设定数据表(setDT)(df)[, y := fcase(!x %in% c(88, 99), x, x == 88, 0)]
<details>
<summary>英文:</summary>
Using `fcase`
library(data.table)
setDT(df)[, y := fcase(!x %in% c(88, 99), x, x == 88, 0)]
答案3
得分: 0
使用 tidyverse 软件包（例如 dplyr 和 tidyr），您有多种选择。其中一种选择是使用 na_if 将 99 转换为 NA，并使用 if_else 将 88 转换为 0。
我已经创建了一个虚拟数据集如下，但如果您对特定数据集有疑问，应提供一个具有您自己数据的可重现示例。
library(tidyverse)
a <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = TRUE)
b <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = TRUE)
c <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = TRUE)
df <- data.frame(a, b, c)
df
df %>%
mutate(across(everything(), ~na_if(., 99))) %>%
mutate(across(everything(), ~if_else(. == 88, 0, .)))
只有代码部分已被翻译。
英文:
You have a lot of options at your disposal with the tidyverse packages (e.g., dplyr, tidyr). One option is to use na_if to turn the 99s into NA and if_else to turn the 88s to 0.
I have created a fake dataset below, but if you have questions about your specific dataset, you should provide a reproducible example with your own data.
library(tidyverse)
a <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = T)
b <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = T)
c <- sample(x = c(1, 2, 3, 4, 99, 88), size = 30, replace = T)
df <- data.frame(a, b, c)
df
df %>%
mutate(across(everything(), ~na_if(., 99))) %>%
mutate(across(everything(), ~if_else(. == 88, 0, .)))
答案4
得分: 0
我们可以使用基本的 R 代码来就地更新匹配的值。
df$y[df$y == 99] <- NA
df$y[df$y == 88] <- 0
英文:
We can update matching values inplace with base R
df$y[df$y == 99] <- NA
df$y[df$y == 88] <- 0
</details>
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