Data frame subset according to matching values in R - r

Question

I have a data.frame with information on racing performance on horses. I have a variable Competition.year that has a "Total" row and then a row for each year the horse competed. I also have a variable Competition.age that describes the age the horses were in each specific year they competed.
I am trying to create a subsetted df based on their best racing times and the age they were when they achieved it. In the "Total" row, the racing time included is their best one. So, I need to figure out how to tell R that, when the race time in Total row is equal to whenever it is they actually achieved that time, include the age they were then in the new data frame. I am super new to R so I have no idea where to even begin doing this, I've tried some stuff I've seen on other questions but I can't get it right. Any help would be much appreciated!
My df looks like this:
travdata <- data.frame(
"Name"=c(rep("Muuttuva",3),rep("Pelson Poika",7),rep("Muusan Muisto",4)),
"Competition.year" = c("Total",2005,2004,"Total",2003,2004,2006,2005,2002,2001,2008,2010,"Total",2009),
"Time.record.auto.start"=c(93.5,NA,93.5,96.5,NA,NA,104.2,96.5,NA,96.6,NA,NA,NA,NA),
"Time.record.volt.start"=c(92.5,98.4,92.5,94.3,NA,105.3,98.3,94.3,102.1,99.1,107.5,NA,107.5,NA),
"Competition.age"=c(NA,6,7,NA,4,5,6,7,8,9,NA,5,6,7))
The desired df should have 223 rows (since that is the total amount of horses I have) with columns Name, Competition.year=="Total", Time.record.auto.start, Time.record.volt.start and Competition.age

Answer 1

Firstly, I had to change your sample data to make sure all 5 variables only had 14 observations each. I did this by removing the final NA in the Competition.age variable. I also had to swap around the 94.3 and 98.3 values in the Time.record.volt.start variable so that the values lined up with what was expected in the Total column for the horse with Name equal to Pelson Poika.
Here is the corrected data:
travdata <- data.frame(
"Name"=c(rep("Muuttuva",3),rep("Pelson Poika",7),rep("Muusan Muisto",4)),
"Competition.year" = c("Total",2005,2004,"Total",2003,2004,2006,2005,2002,2001,2008,2010,"Total",2009),
"Time.record.auto.start"=c(93.5,NA,93.5,96.5,NA,NA,104.2,96.5,NA,96.6,NA,NA,NA,NA),
"Time.record.volt.start"=c(92.5,98.4,92.5,94.3,NA,105.3,98.3,94.3,102.1,99.1,107.5,NA,107.5,NA),
"Competition.age"=c(NA,6,7,NA,4,5,6,7,8,9,NA,5,6,7))
And here is a simple dplyr solution, which I think does what you want.
library(dplyr)
df1 <-
travdata %>% group_by(Name) %>% filter(Competition.year == "Total") %>% select(Name, Time.record.auto.start, Time.record.volt.start)
df2 <- travdata %>% filter(Competition.year != "Total")
df3 <-
inner_join(
df1,
df2,
by = c(
"Name" = "Name",
"Time.record.auto.start" = "Time.record.auto.start",
"Time.record.volt.start" = "Time.record.volt.start"
)
)
The dataframe df3 should return what you were after.