Change value in grouping based on condition - r

Question

I'm starting with the following data:
df <- data.frame(Person=c("Ada","Ada","Bob","Bob","Carl","Carl"), Day=c(1,2,2,1,1,2), Fruit=c("Apple","X","Apple","X","X","Orange"))
Person Day Fruit
1 Ada 1 Apple
2 Ada 2 X
3 Bob 2 Apple
4 Bob 1 X
5 Carl 1 X
6 Carl 2 Orange
And I want to loop through every person and replace the unknown fruit X with either Apple or Orange while making sure that if it's Orange one day, it should be Apple the next day, and vice versa.
For Ada: Day 1 = Apple, meaning Day 2 = X <- Orange
I don't know where to start other than:
library(dplyr)
df %>%
group_by(Person)
any suggestions for direction?

Answer 1

Another solution using case_when from dplyr:
library(dplyr)
# Changing datatypes to character instead of factor
df[] <- lapply(df, as.character)
# Optional, but this line will convert all columns to appropriate datatype, eg. Day will be integer
df <- readr::type_convert(df)
df %>%
group_by(Person) %>%
mutate(
Contains_Apple = any(Fruit == "Apple"),
Contains_Orange = any(Fruit == "Orange"),
Fruit = case_when(
Fruit == "X" & Contains_Apple == F ~ "Apple",
Fruit == "X" & Contains_Orange == F ~ "Orange",
TRUE ~ Fruit
)
)
# A tibble: 6 x 5
# Groups: Person [3]
Person Day Fruit Contains_Apple Contains_Orange
<chr> <int> <chr> <lgl> <lgl>
1 Ada 1 Apple T F
2 Ada 2 Orange T F
3 Bob 2 Apple T F
4 Bob 1 Orange T F
5 Carl 1 Apple F T
6 Carl 2 Orange F T
Remove the Contains_Apple and Contains_Orange by:
df %>%
group_by(Person) %>%
mutate(Contains_Apple = any(Fruit == "Apple"),
Contains_Orange = any(Fruit == "Orange"),
Fruit = case_when(Fruit == "X" & Contains_Apple == F ~ "Apple",
Fruit == "X" & Contains_Orange == F ~ "Orange",
TRUE ~ Fruit)) %>%
select(Person, Day, Fruit) %>%
ungroup()
# A tibble: 6 x 3
Person Day Fruit
<chr> <int> <chr>
1 Ada 1 Apple
2 Ada 2 Orange
3 Bob 2 Apple
4 Bob 1 Orange
5 Carl 1 Apple
6 Carl 2 Orange

Answer 2

Here is one idea using case_when to check if each group already has "Apple" or "Orange", and then assign the opposite value if Fruit is "X".
Notice that I added stringsAsFactors = FALSE when creating the example data frame, which aims to avoid the creation of factor columns.
library(dplyr)
library(tidyr)
df %>%
group_by(Person) %>%
mutate(Fruit = case_when(
Fruit %in% "X" & any(Fruit %in% "Apple") ~ "Orange",
Fruit %in% "X" & any(Fruit %in% "Orange") ~ "Apple",
TRUE ~ Fruit
)) %>%
ungroup()
# # A tibble: 6 x 3
# Person Day Fruit
# <chr> <dbl> <chr>
# 1 Ada 1.00 Apple
# 2 Ada 2.00 Orange
# 3 Bob 2.00 Apple
# 4 Bob 1.00 Orange
# 5 Carl 1.00 Apple
# 6 Carl 2.00 Orange
DATA
df <- data.frame(Person=c("Ada","Ada","Bob","Bob","Carl","Carl"),
Day=c(1,2,2,1,1,2),
Fruit=c("Apple","X","Apple","X","X","Orange"),
stringsAsFactors = FALSE)

Answer 3

Simple with looping:
fruity_loop <- function(frame) {
ops <- c('Apple', 'Orange')
for(x in 1:nrow(frame)) {
if(frame[x,]['Fruit'] == 'X') {
if(frame[x-1,]['Fruit'] == ops[1]) { frame[x,]['Fruit'] <- ops[2] } else { frame[x,]['Fruit'] <- ops[1] } }
}
return(frame)
}
Example:
fruity_loop(df)