There are some awesome packages for working with time data. Try this:
library(tidyverse)
library(lubridate)
library(xts)
my_datatable <- tribble(
~admissions, ~ Date,
151, '2020-03-19',
89, '2020-03-20',
104, '2020-03-21',
125, '2020-03-22',
155, '2020-03-23'
) %>%
mutate(Date = ymd(Date))
my_date_info <- my_datatable %>% pull(Date)
my_time_series_data <- my_datatable %>%
xts(x = ., order.by = my_date_info)
Then you can graph your data with something like:
library(dygraphs)
my_time_series_data[,'admissions'] %>% dygraph()
And run an acf or pacf like:
pacf(my_datatable[,'admissions'])