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| library(tidyverse) | |
| # Read CSV file | |
| df <- read_csv("https://raw.githubusercontent.com/lennymd/formulaOneAnalysis/main/data/race_results_statsf1.csv") %>% filter(year == 1950) | |
| # Trying to calculate for the last place for a race | |
| get_dead_last <- function(some_race_id) { | |
| last <- df %>% | |
| select(race_id, position, driver) %>% | |
| filter(race_id == some_race_id) %>% | |
| filter(position != "&") %>% | |
| distinct(race_id,driver) %>% | |
| summarise(count=n()) %>% | |
| pull(count) | |
| return(last) | |
| } | |
| # If I run this for a specific race, I do get the right value. For the first race it should be 23. | |
| cat(get_dead_last(1)) | |
| # But when I try to apply it to my dataset, I get a huge value for every row. | |
| # How can I fix that? | |
| df2 <- df %>% rowwise() %>% mutate(last_place = get_dead_last(race_id)) | |
| # Things seem to work, but if it goes row by row, it'd have to do that 25k times. | |
| View(df2) | |
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