dplyr error - works fine with excell import but doesn't with db import

[Slavek]

Hi,
I have a project where a testing file I was working on was saved in excel. Now I run the same code for exactly the same data but taken directly from the database and the code is not working.

The code I run is:

result <- merged.comments %>% 
  mutate(Blank = ifelse(test = (is.na(x = merged.comments$all_comment)),yes = 1,
                        no = ifelse((test = (str_length(string = merged.comments$all_comment) < 5) | (str_detect(string = all_comment,pattern = blank_statements))|(str_detect(all_comment, "(.)\\1{3,}"))),yes = 1,no = 0)),
         As_above = if_else(str_detect(all_comment, previous_statements), 1, 0),
         Blank_AComm_1 = ifelse(test = (is.na(x = merged.comments$AComm_1)),yes = 1,
                        no = ifelse((test = (str_length(string = merged.comments$AComm_1) < 5) | (str_detect(string = AComm_1,pattern = blank_statements))|(str_detect(AComm_1, "(.)\\1{3,}"))),yes = 1,no = 0)),
         As_above_AComm_1 = if_else(str_detect(AComm_1, previous_statements), 1, 0)) %>% 
  mutate_if(is.numeric, ~if_else(is.na(.), 0, .))

and error is:

Error: `false` must be a double vector, not an integer vector

Very weird because when I export the source of data to Excel and import again (from excel), the code works fine without any error.
The database is to big to give you access to data or an example.

Does R environment work differently when the same data is taken from different resources?

[Yarnabrina]

Can you please check whether this code works for you or not?

result <- merged.comments %>% 
  mutate(Blank = ifelse(test = (is.na(x = merged.comments$all_comment)),yes = 1,
                        no = ifelse((test = (str_length(string = merged.comments$all_comment) < 5) | (str_detect(string = all_comment,pattern = blank_statements))|(str_detect(all_comment, "(.)\\1{3,}"))),yes = 1,no = 0)),
         As_above = if_else(str_detect(all_comment, previous_statements), 1, 0),
         Blank_AComm_1 = ifelse(test = (is.na(x = merged.comments$AComm_1)),yes = 1,
                        no = ifelse((test = (str_length(string = merged.comments$AComm_1) < 5) | (str_detect(string = AComm_1,pattern = blank_statements))|(str_detect(AComm_1, "(.)\\1{3,}"))),yes = 1,no = 0)),
         As_above_AComm_1 = if_else(str_detect(AComm_1, previous_statements), 1, 0)) %>% 
  mutate_if(is.numeric, ~ifelse(is.na(.), 0, .))

The only change I made is that I changed if_else to ifelse, as it seemed to me that the last line is creating the problem because of strict type requirements of if_else.

If this does not work, can you please provide a REPRoducible EXample of your problem? It provides more specifics of your problem, and it helps others to understand what problem you are facing.

If you don't know how to do it, take a look at this thread:

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.…

[gabriel.de.wit]

Or if you want to keep if_else as opposed to ifelse then maybe have two separate mutate_ifs - one for integers, one for doubles:

mutate_if(is.double, ~if_else(is.na(.), 0, .)) %>%
mutate_if(is.integer, ~if_else(is.na(.), 0L, .))

I'm guessing that there are columns which are stored as integers in the database, and so R reads them as integers, whereas the Excel file had everything stored as decimals due to number formatting or similar.