GaB
Reputation: 1134
how to add a new column based on certain conditions with tidyverse?
I am trying to create a new column based on whether a respondent is healthy or not.
Here it the type fo data I have:
test <- structure(list(`cutree(hc_diana, k = 4)` = c(1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), id = c("117dbbbf15", "117dbbbf15", "117dbbbf15", "117dbbbf15",
"117dbbbf15", "117dbbbf15", "117dbbbf15", "117dbbbf15", "117dbbbf15",
"3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3",
"3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "8a594e9340",
"8a594e9340"), covid_tested = c("positive", "positive", "positive",
"positive", "positive", "positive", "positive", "positive", "positive",
"positive", "positive", "positive", "positive", "positive", "positive",
"positive", "positive", "positive", "positive", "positive"),
age = c(51, 51, 51, 51, 51, 51, 51, 51, 51, 28, 28, 28, 28,
28, 28, 28, 28, 28, 28, 28), gender = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("Female", "Male", "Other"), class = "factor"),
number_morbidities = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1), chills = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("No", "Yes"), class = "factor"), cough = structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
diarrhoea = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), fatigue = structure(c(2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
headache = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), loss_smell_taste = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"),
muscle_ache = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), nasal_congestion = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
nausea_vomiting = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), shortness_breath = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
sore_throat = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), sputum = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("No", "Yes"), class = "factor"), temperature = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
loss_appetite = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), chest_pain = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
itchy_eyes = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("No",
"Yes"), class = "factor"), joint_pain = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"),
comorbidities = c("asthma", "diabetes_type_one", "diabetes_type_two",
"obesity", "hypertension", "heart_disease", "lung_condition",
"liver_disease", "kidney_disease", "asthma", "diabetes_type_one",
"diabetes_type_two", "obesity", "hypertension", "heart_disease",
"lung_condition", "liver_disease", "kidney_disease", "asthma",
"diabetes_type_one"), bolean_yes_no = c("No", "No", "No",
"Yes", "No", "No", "No", "No", "No", "No", "No", "No", "No",
"No", "No", "No", "No", "No", "No", "No")), row.names = c(NA,
-20L), class = c("tbl_df", "tbl", "data.frame"))
I have 15 rows with 3 unique id's in Yet, I want to get new column based on several conditions:
- if they have a comorbidity -> then select only the row with that comorbidity in question and add it into the new column with its name, yet all the other should have NA
- as you can see the second id , does not have whatsoever any comorbidity, therefore I want a new category for it and treat it as a "healthy" category and the rest of the rows pertaining to this patient to appear as NA. This is the same for the third responder.
How do I do this with tidyverse?
A sample of how I want the new column to look like is here, check the last column that summarises the above points.
structure(list(id = c("117dbbbf15", "117dbbbf15", "117dbbbf15",
"117dbbbf15", "117dbbbf15", "117dbbbf15", "117dbbbf15", "117dbbbf15",
"117dbbbf15", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3",
"3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3", "3c8bfb6fc3",
"8a594e9340", "8a594e9340"), number_morbidities = c(1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1), chills = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), cough = structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), diarrhoea = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), fatigue = structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), headache = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), loss_smell_taste = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L), .Label = c("No", "Yes"), class = "factor"), muscle_ache = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), nasal_congestion = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), nausea_vomiting = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), shortness_breath = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), sore_throat = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), sputum = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), temperature = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), loss_appetite = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), chest_pain = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), itchy_eyes = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), joint_pain = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("No", "Yes"), class = "factor"), comorbidities = c("asthma",
"diabetes_type_one", "diabetes_type_two", "obesity", "hypertension",
"heart_disease", "lung_condition", "liver_disease", "kidney_disease",
"asthma", "diabetes_type_one", "diabetes_type_two", "obesity",
"hypertension", "heart_disease", "lung_condition", "liver_disease",
"kidney_disease", "asthma", "diabetes_type_one"), bolean_yes_no = c("No",
"No", "No", "Yes", "No", "No", "No", "No", "No", "No", "No",
"No", "No", "No", "No", "No", "No", "No", "No", "No"), morbiditiy_healthy = c(NA,
NA, NA, "obesity", NA, NA, NA, NA, NA, "healthy", NA, NA, NA,
NA, NA, NA, NA, NA, "healthy", NA)), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame"))
Upvotes: 1
Views: 470
Answers (1)
akrun
Reputation: 887961
We group by 'id', create the 'morbidity_healthy' with case_when where we check for 'Yes' in 'bolean_yes_no' column, if it is TRUE, then get the corresponding 'comorbidities', and if there are not (!) any 'Yes' and the row_number is 1, then return the 'healthy' for that row
library(dplyr)
test %>%
group_by(id) %>%
mutate(morbidity_healthy = case_when(bolean_yes_no == 'Yes' ~ comorbidities,
(!any(bolean_yes_no == 'Yes')) & row_number()==1 ~ 'healthy'))
Upvotes: 1
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