Access R Dataframe Values Rather than Tibble - r

Question

I'm an experienced Pandas user and am having trouble plugging values from my R frame into a function.
The following function works with hard coded values
>seq.Date(as.Date('2018-01-01'), as.Date('2018-01-31'), 'days')
[1] "2018-01-01" "2018-01-02" "2018-01-03" "2018-01-04" "2018-01-05" "2018-01-06" "2018-01-07"
[8] "2018-01-08" "2018-01-09" "2018-01-10" "2018-01-11" "2018-01-12" "2018-01-13" "2018-01-14"
[15] "2018-01-15" "2018-01-16" "2018-01-17" "2018-01-18" "2018-01-19" "2018-01-20" "2018-01-21"
[22] "2018-01-22" "2018-01-23" "2018-01-24" "2018-01-25" "2018-01-26" "2018-01-27" "2018-01-28"
[29] "2018-01-29" "2018-01-30" "2018-01-31"
Here is an extract from a dataframe I'm using
>df[1,1:2]
# A tibble: 1 x 2
start_time end_time
<date> <date>
1 2017-04-27 2017-05-11
When plugging these values into the 'seq.Date' function I get an error
> seq.Date(from=df[1,1], to=df[1,2], 'days')
Error in seq.Date(from = df[1, 1], to = df[1, 2], "days") :
'from' must be a "Date" object
I suspect this is because subsetting using df[x,y] returns a tibble rather than the specific value
data.class(df[1,1])
[1] "tbl_df"
What I'm hoping to derive is a sequence of dates. I need to be able to point this at various places around the dataframe.
Many thanks for any help!

Answer 1

Just use double brackets:
seq.Date(from=df[[1,1]], to=df[[1,2]], 'days')

Answer 2

The extraction functions of tibble may not return vectors but one column tibbles, use dplyr::pull to extract the column as vector, like in this answer: Extract a dplyr tbl column as a vector

Answer 3

Another option is to set the drop argument in the `[` function to TRUE.
If TRUE the result is coerced to the lowest possible dimension
seq.Date(from = df[1, 1, drop = TRUE], to = df[1, 2, drop = TRUE], 'days')
# [1] "2017-04-27" "2017-04-28" "2017-04-29" "2017-04-30" "2017-05-01" "2017-05-02" "2017-05-03" "2017-05-04" "2017-05-05" "2017-05-06"
#[11] "2017-05-07" "2017-05-08" "2017-05-09" "2017-05-10" "2017-05-11"
data
df <- tibble(start_time = as.Date('2017-04-27'),
end_time = as.Date('2017-05-11'))