This is the best formula:
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats 1.0.0 ✔ readr 2.1.5
✔ ggplot2 3.5.1 ✔ stringr 1.5.1
✔ lubridate 1.9.4 ✔ tibble 3.2.1
✔ purrr 1.0.4 ✔ tidyr 1.3.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
# A tibble: 4 × 5
`Date Received` `Requesting Unit` Recipient Location `Document Type`
<dttm> <chr> <chr> <chr> <chr>
1 2023-01-23 00:00:00 HRMD DOF Manila Others_ urgent
2 2023-01-23 00:00:00 HRMD DOF Manila Others_ urgent
3 2023-01-23 00:00:00 HRMD CSC QC Admin doc
4 2023-01-24 00:00:00 HRMD DOF Manila Financial_ routinary