R: if_else, ifelse - r

Question

Am new to R and getting to it after a long time as well.
I got the NFL week 1 data from the site and trying to execute a small ifelse and it doesn't work.
I want the team name in the result field
#this works only when condition is true and doesn't when condition is false
wk1$tm_won= if_else(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#this doesn't work - gives me the difference
wk1$tm_won1 <- ifelse(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#this doesn't work - gives me difference and not the team name
wk1 %>%
mutate(tm_won2 = ifelse (home_score < away_score, away_team,
ifelse (home_score > away_score, home_team, NA)))
#this doesn't work
wk1 %>%
mutate(tm_won = case_when(
home_score < away_score ~ away_team,
home_score > away_score ~ home_team,
TRUE ~ a ))# DRAW
My result dataset:
season week home_team away_team home_score away_score tm_won tm_won1 tm_won2
2019 1 CHI GB 3 10 GB 7 7
2019 1 CAR LA 27 30 LA 11 11
2019 1 PHI WAS 32 27 <NA> 14 14
2019 1 NYJ BUF 16 17 BUF 3 3
2019 1 MIN ATL 28 12 <NA> 9 9

Answer 1

What's happening here is that your teams are actually factors (which under the hood are just integer vectors) instead of characters. If the columns are characters, essentially all of your solutions work as expected. The reason the output is different is because dplyr tries to be clever about factors and keep them human-readable when it can.
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
wk1 <- read.table(text = 'season week home_team away_team home_score away_score tm_won tm_won1 tm_won2
2019 1 CHI GB 3 10 GB 7 7
2019 1 CAR LA 27 30 LA 11 11
2019 1 PHI WAS 32 27 <NA> 14 14
2019 1 NYJ BUF 16 17 BUF 3 3
2019 1 MIN ATL 28 12 <NA> 9 9', header = T, stringsAsFactors = FALSE)
if_else(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#> [1] "GB" "LA" "PHI" "BUF" "MIN"
ifelse(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#> [1] "GB" "LA" "PHI" "BUF" "MIN"
wk1 <- read.table(text = 'season week home_team away_team home_score away_score tm_won tm_won1 tm_won2
2019 1 CHI GB 3 10 GB 7 7
2019 1 CAR LA 27 30 LA 11 11
2019 1 PHI WAS 32 27 <NA> 14 14
2019 1 NYJ BUF 16 17 BUF 3 3
2019 1 MIN ATL 28 12 <NA> 9 9', header = T)
if_else(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#> Warning in `[<-.factor`(`*tmp*`, i, value = structure(c(5L, 3L), .Label =
#> c("CAR", : invalid factor level, NA generated
#> [1] GB LA <NA> BUF <NA>
#> Levels: ATL BUF GB LA WAS
ifelse(wk1$home_score < wk1$away_score, wk1$away_team, wk1$home_team)
#> [1] 3 4 5 2 3
Created on 2019-10-09 by the reprex package (v0.3.0)

Answer 2

Another option is to use as.character in the if_else
dplyr::if_else(wk1$home_score < wk1$away_score,
as.character(wk1$away_team),
as.character(wk1$home_team))