recoding items in the data doesn't work

[Laura2]

Hello,

I have three items that need to be recoded:
data$tweede_lockdown_1_w2<-as.factor(recode_factor(data$tweede_lockdown_1_w2,'2'='1', '3'='2','6'='3','7'='4','8'='5'))
data$tweede_lockdown_2_w2.r<-as.factor(recode_factor(data$tweede_lockdown_2_w2.r,'2'='1', '3'='2','6'='3','7'='4','8'='5'))
data$tweede_lockdown_3_w2<-as.factor(recode_factor(data$tweede_lockdown_3_w2,'2'='1', '3'='2','6'='3','7'='4','8'='5'))
But, when I do that, I see that nothing has changed in the data.

Does anyone know what I should do differently?

Thanks in advance!

[nirgrahamuk]

although the use of as.factor is unecesary and can be removed, and the mix of dplyr and base R seems odd (given the particular context where the same transformation is repeated and purer dplyr use would be more concise), I can't see anything syntactically wrong with your code to where it wouldnt be changing.

# example data 
data <- data.frame(tweede_lockdown_1_w2=factor(2))

testing:

>data$tweede_lockdown_1_w2
[1] 2
Levels: 2

your code:

data$tweede_lockdown_1_w2 <- as.factor(recode_factor(data$tweede_lockdown_1_w2,'2'='1', '3'='2','6'='3','7'='4','8'='5'))

testing:

> data$tweede_lockdown_1_w2
[1] 1
Levels: 1

[Laura2]

Thank you for your response!

The problem is that although I recoded for example the 2 to 1, it seems like it hasn't changed, because the minimum value is still 2 and the maximum value is 8 (which should not be possible, because the maximum value I insurted was 5).

summary(dataset$tweede_lockdown_1_w2)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
2.000 6.000 7.000 6.454 8.000 8.000 127

summary(dataset$tweede_lockdown_2_w2)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
2.000 3.000 6.000 5.448 7.000 8.000 126
summary(dataset$tweede_lockdown_3_w2)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
2.00 2.00 3.00 4.13 6.00 8.00 127

Would you know what I could do to change this?

Thank you for your time!

[nirgrahamuk]

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…