How do I make new columns for data across time using the variables from an original column?

Question

I have R code that takes raw data where each patient entry is one row, and sums it up for a 'frequency' column for each department by date.

What I used here was the code:

department_totals <- as.data.frame(count(sheet, c("Date", "Department")))

To get:

Department	Date	Frequency
Dental	14 Mar	5
Dental	15 Mar	3
Dental	16 Mar	2
Cardio	14 Mar	4
Cardio	15 Mar	7
Cardio	16 Mar	8
Physio	14 Mar	1
Physio	16 Mar	2

But for this new project, I need it to be the actual individual departments by date, like this:

Date	Dental	Cardio	Physio
14 Mar	5	4	1
15 Mar	3	7	blank
16 Mar	2	8	2

And I can't figure out how to do it. I can group by department, but I'm trying to make each unique variable in 'Department' its own variable and then have the frequency of variables for each of those as a new column, ordered by date.

The intent here is to be able to make line graphs of how each of these departments' frequency of patients changes over time.

score 0 · Answer 1 · answered May 31 '22 at 07:05

library(tidyverse)
df %>% pivot_wider(names_from = Department, values_from = Frequency)


# A tibble: 3 x 4
  Date   Dental Cardio Physio
  <chr>   <int>  <int>  <int>
1 14_Mar      5      4      1
2 15_Mar      3      7     NA
3 16_Mar      2      8      2

How do I make new columns for data across time using the variables from an original column?

1 Answers1