How do I coerce a tibble dataframe column from double to time? - r

Question

I'm in the tidyverse.
I read in several CSV files using read_csv (all have the same columns)
df <- read_csv("data.csv")
to obtain the a series of dataframes. After a bunch of data cleaning and calculations, I want to merge all the dataframes.
There are a dozen dataframes of several hundred rows, and a few dozen columns. A minimal example is
DF1
ID name costcentre start stop date
<chr> <chr> <chr> <time> <tim> <chr>
1 R_3PMr4GblKPV~ Geo Prizm 01:00 03:00 25/12/2019
2 R_s6IDep6ZLpY~ Chevy Malibu NA NA NA
3 R_238DgbfO0hI~ Toyota Corolla 08:00 11:00 25/12/2019
DF2
ID name costcentre start stop date
<chr> <chr> <chr> <lgl> <time> <chr>
1 R_3PMr4GblKPV1OYd Geo Prizm NA NA NA
2 R_s6IDep6ZLpYvUeR Chevy Malibu NA 03:00 12/12/2019
3 R_238DgbfO0hItPxZ Toyota Corolla NA NA NA
Based on my cleaning requirements (is start == NA & stop != NA), some of the NAs in start must be 00:00. I can enter a zero in that cell:
df <- within(df, start[is.na(df$start) & !is.na(df$stop)] <- 0)
This results in
DF1
ID name costcentre start stop date
<chr> <chr> <chr> <time> <tim> <chr>
1 R_3PMr4GblKPV~ Geo Prizm 01:00 03:00 25/12/2019
2 R_s6IDep6ZLpY~ Chevy Malibu NA NA NA
3 R_238DgbfO0hI~ Toyota Corolla 08:00 11:00 25/12/2019
DF2
ID name costcentre start stop date
<chr> <chr> <chr> <dbl> <time> <chr>
1 R_3PMr4GblKPV1OYd Geo Prizm NA NA NA
2 R_s6IDep6ZLpYvUeR Chevy Malibu 0 03:00 12/12/2019
3 R_238DgbfO0hItPxZ Toyota Corolla NA NA NA
I run into issues on merging, as sometimes start is a double (as I've done some replacements), is logical (as there were all NAs with no replacements), or is time (if there were some times in the original data reading)
merged_df <- bind_rows(DF1, DF2,...)
gives me the error Error: Columnstartcan't be converted from hms, difftime to numeric
How do I coerce the start column to be of the type time so that I may merge my data?

Answer 1

I think the important point is that the columns start and stop, which appear to be of type time, are based on the hms package. I wondered why/when is displayed, becauses I had not heared about this class before.
As I see it, these columns are actually of class hms and difftime. Such objects are actually stored not in minutes (as the printed tibble suggests) but in seconds. We see this if we look at the data via View(df). Interestingly, if we print the data, the variable type is displayed as time.
To solve your problem, you have to convert all your start and stop columns consistently into hms difftime columns as in the example below.
Minimal reproducible example:
library(dplyr)
library(hms)
df1 <- tibble(id = 1:3,
start = as_hms(as.difftime(c(1*60,NA,8*60), units = "mins")),
stop = as_hms(as.difftime(c(3*60,NA,11*60), units = "mins")))
df2 <- tibble(id = 4:6,
start = c(NA,NA,NA),
stop = as_hms(as.difftime(c(NA,3*60,NA), units = "mins")))
Or even easier (but with slightly different printing than in the question):
df1 <- tibble(id = 1:3,
start = as_hms(c(1*60,NA,8*60)),
stop = as_hms(c(3*60,NA,11*60)))
df2 <- tibble(id = 4:6,
start = c(NA,NA,NA),
stop = as_hms(c(NA,3*60,NA)))
Solving the problem:
class(df1$start) # In df1 start has class hms and difftime
class(df2$start) # In df2 start has class logical
# We set start=0 if stop is not missing and turn the whole column into an hms object
df2 <- df2 %>% mutate(start = new_hms(ifelse(!is.na(stop), 0, NA)))
# Now that column types are consistent across tibbles we can easily bind them together
df <- bind_rows(df1, df2)
df