英文:
how to apply changes to existing data variables
问题
我执行了很多数据转换操作，其中一个让我遇到了一些麻烦。
假设我有一个数据集，其中包含从v1到v100的变量，每个变量的取值范围是1到5。我想要重新编码/更改一些变量（例如从v10到v20）。
我经常使用dplyr包，还有一些来自Daniel Ludecke的其他包，比如sjmisc、sjPlot、sjlabelled等。
如何将这个操作的结果发送到最初的数据集中，覆盖原来的位置（即进行覆盖操作）？
我不想创建额外的变量（例如v10_r、v11_r等），只想进行覆盖操作。我对数据集进行了很多这样的类似更改，希望能够尽可能简单地应用它们。
英文:
I perform lots of data transformation and one of them makes me some troubles.
Let's assume that I have a dataset with variavles from v1 to v100, every one with numbers from 1 to 5. I want to recode/change some of variables (for example from v10 to v20)
I use dplyr package a lot and some another coming from Daniel Ludecke, i.e. sjmisc, sjPlot, sjlabelled etc.
dataset %>%
select(v10:v20) %>%
rec(rec = "1:2=1;3:5=2")
How to send the result of this operation to the initial dataset to the same place from which they were retrieved (this will be an overwrite)?
I don't want to create additional variable (i.e. v10_r, v11_r etc), just overwrite. I make a lot of these and similar changes to a dataset and would like to be able to apply them as simply as possible.
答案1
得分: 2
你可以使用dplyr包中的mutate_at函数来实现这个目标：
library(dplyr)
dataset <- dataset %>%
mutate_at(vars(v10:v20), ~ recode(.x, `1:2` = 1, `3:5` = 2))
这将直接修改原始数据集，在v10到v20的变量上用重新编码的值进行覆盖。
英文:
You can achieve this using the mutate_at function from the dplyr package:
library(dplyr)
dataset <- dataset %>%
mutate_at(vars(v10:v20), ~ recode(.x, `1:2` = 1, `3:5` = 2))
This will modify the original dataset in place, overwriting the variables from v10 to v20 with the recoded values.
答案2
得分: 2
另一个选项是使用dplyr中的case_match，它有效地替代了recode：
library(dplyr)
df %>%
mutate(across(v10:v20,
~ case_match(.x,
1:2 ~ 1,
3:5 ~ 2)))
或者你也可以使用dplyr中的case_when，但比使用case_match稍微冗长一些。
df %>%
mutate(across(v10:v20,
~ case_when(.x %in% (1:2) ~ 1,
.x %in% (3:5) ~ 2)))
英文:
Another option is to use case_match from dplyr, which effectively replaced recode:
library(dplyr)
df %>%
mutate(across(v10:v20,
~ case_match(.x,
1:2 ~ 1,
3:5 ~ 2)))
Or you can also use case_when from dplyr, but slightly more verbose than using case_match.
df %>%
mutate(across(v10:v20,
~ case_when(.x %in% (1:2) ~ 1,
.x %in% (3:5) ~ 2)))
通过集体智慧和协作来改善编程学习和解决问题的方式。致力于成为全球开发者共同参与的知识库，让每个人都能够通过互相帮助和分享经验来进步。
评论