Finding solution to mutate error message

[Laju]

Riding_time

Hi everyone,

I tried running the below codes and I'm getting an error message. Checking if anyone can help prefer a solution. Looking forward to your feedback. Thanks!

Code:

clean_dfs <- new_binded_dfs_no_dups
clean_dfs <- clean_dfs %>%
  mutate(riding_time = as.numeric(end_hours-start_hours)/60)

clean_dfs 

Error Message:
Error in mutate(): ! Problem while computing riding_time = as.numeric(end_hours - start_hours)/60. Caused by error: ! object 'end_hours' not found Backtrace: 1. clean_dfs %>% ... 3. dplyr:::mutate.data.frame(...) 4. dplyr:::mutate_cols(.data, dplyr_quosures(...), caller_env = caller_env()) 6. mask$eval_all_mutate(quo)

[image] Show Traceback

Error in mutate(., riding_time = as.numeric(end_hours - start_hours)/60) : Caused by error: ! object 'end_hours' not found.

Note:
Kindly note that I had previously created the 'start_hours' & 'end_hours' columns using the below codes:

Start_hours & End_hours

clean_dfs <- clean_dfs %>%
  mutate(start_hours=strftime(clean_dfs$started_at, format = "%H:%M:%S",tz = "UTC"))

clean_dfs <- clean_dfs %>%
  mutate(end_hours=strftime(clean_dfs$ended_at, format = "%H:%M:%S",tz = "UTC"))
clean_dfs

[pieterjanvc]

Hi,

Welcome to the RStudio community!

It would be easier to find the source of this error if you could provide us with a reprex. A reprex consists of the minimal code and data needed to recreate the issue/question you're having. You can find instructions how to build and share one here:

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.…

The error now occurs because there is no end_hours in your data frame, but you show below you create this using the clean_dfs mutate. However, this line seems problematic:

clean_dfs <- new_binded_dfs_no_dups

You overwrite the clean_dfs with data from another variable, so even if you did change it before, it will revert to this one (and thus lose the mutated variables probably).

Please provide a reprex if this is not the issue
PJ