CODEWITHSUNDEEP
r
Natasha H
Natasha H

Reputation: 69

How can I create a function in R that calculations across rows?

I have a dataset that looks similar to this:

Patient ID Unit Type Status
1234 ABC Returned
1234 ABC Returned
1234 ABC Returned
1234 ABC Returned
1234 ABC Transfused
1234 DEF Transfused
1234 DEF Transfused
1234 DEF Transfused
1234 GHI Transfused

Table Code:

> dput(df)
structure(list(Patient_ID = c("1234", "1234", "1234", "1234", 
"1234", "1234", "1234", "1234", "1234"), Unit_Type = c("ABC", 
"ABC", "ABC", "ABC", "ABC", "DEF", "DEF", "DEF", "GHI"), Status = c("Returned", 
"Returned", "Returned", "Returned", "Transfused", "Transfused", 
"Transfused", "Transfused", "Transfused")), class = "data.frame", row.names = c(NA, 
-9L))

I want my output to look like this (preferably in a new dataframe):

Patient ID ABC_Returned ABC_Transfused DEF_Tranfused GHI_Transfused
1234 4 1 3 1

How can I create a function that would automate this process?

Upvotes: 0

Views: 30

Answers (2)

Jon Spring
Jon Spring

Reputation: 67050

library(tidyverse)
df %>%
  count(Patient_ID, Unit_Type, Status) %>%
  pivot_wider(names_from = c(Unit_Type, Status), values_from = n)

result

# A tibble: 1 × 5
  Patient_ID ABC_Returned ABC_Transfused DEF_Transfused GHI_Transfused
  <chr>             <int>          <int>          <int>          <int>
1 1234                  4              1              3              1

Upvotes: 2

Mike
Mike

Reputation: 4400

library(dplyr)


df <- structure(list(Patient_ID = c("1234", "1234", "1234", "1234", 
                              "1234", "1234", "1234", "1234", "1234"), Unit_Type = c("ABC", 
                                                                                     "ABC", "ABC", "ABC", "ABC", "DEF", "DEF", "DEF", "GHI"), Status = c("Returned", 
                                                                                                                                                         "Returned", "Returned", "Returned", "Transfused", "Transfused", 
                                                                                                                                                         "Transfused", "Transfused", "Transfused")), class = "data.frame", row.names = c(NA, 
                                                                                                                                                                                                                                         -9L))  
df2 <- df %>% 
      mutate(unit_stat = paste(Unit_Type, Status, sep = "_")) %>% 
      count(Patient_ID, unit_stat) %>% 
      tidyr::pivot_wider(id_cols = "Patient_ID", names_from = unit_stat, values_from = n)

Upvotes: 1

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