Date range values showing as 'NA'

R code
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1

Hi there, I am using a public health H7N9 dataset. I have tried to clean my hospitalisation date column but the date range is showing as ‘NA’.
I have tried to resolve using the Epi R Handbook but could not find a solution.
Reprex is shown below - Grateful for any help!!

# install and load packages
pacman::p_load(rio, janitor, tidyverse, datapasta, reprex, here)

surv_raw<- data.frame(
         stringsAsFactors = FALSE,
                  case_id = c(1L, 2L, 3L, 4L, 5L),
                      sex = c("m", "m", "f", "f", "f"),
  date_of_hospitalisation = c(NA,"3/3/2013",
                              "3/19/2013","3/27/2013","3/30/2013")
)
# try to convert column to class "Date"
surv_clean <- surv_raw %>% 
  clean_names() %>% 
  mutate(date_of_hospitalisation = mdy(date_of_hospitalisation))


# check the CLEANED date column class and date range
class(surv_clean$date_of_hospitalisation)
#> [1] "Date"
range(surv_clean$date_of_hospitalisation)
#> [1] NA NA

Created on 2024-03-04 with reprex v2.1.0

Session info 
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
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#>  date     2024-03-04
#>  pandoc   3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
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1 Like
2

Hello,

When you are looking at the range of date_of_hospitalisation, you have a NA value which means R defaults to returning NA since it’s unsure whether that value could be smaller than the smallest non-missing value or bigger than the biggest non-missing value. See below for a way to handle this with an argument to the range() function:

# loading packages
library(tidyverse)
library(janitor)
#> 
#> Attaching package: 'janitor'
#> The following objects are masked from 'package:stats':
#> 
#>     chisq.test, fisher.test

# creating fake data
surv_raw <- data.frame(
    stringsAsFactors = FALSE,
    case_id = c(1L, 2L, 3L, 4L, 5L),
    sex = c("m", "m", "f", "f", "f"),
    date_of_hospitalisation = c(NA_character_, "3/3/2013",
                                                            "3/19/2013", "3/27/2013", "3/30/2013")
)

# mutating date
surv_clean <- surv_raw |> 
    clean_names() |>
    mutate(date_of_hospitalisation = mdy(date_of_hospitalisation))

# looking at date
surv_clean |>
    reframe(range_1 = range(date_of_hospitalisation),
                    range_2 = range(date_of_hospitalisation, na.rm = TRUE))
#>   range_1    range_2
#> 1    <NA> 2013-03-03
#> 2    <NA> 2013-03-30

Created on 2024-03-04 with reprex v2.1.0

Session info 
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All the best,

Tim