I found this online and used this with my data:

df <- data.frame(seasons = c("Season1","Season2","Season3","Season4"))
for(i in unique(df$seasons)) {
  df[[paste0(i)]] <- ifelse(df$seasons==i,1,0)
}

The only challenge is where there is a 0 in the resultant cell, I want to fill in a meaningful value from a data frame that has data arranged like so:

Note how a season in a pair could pop up at S1 or S2.

I'll need to fill for example,{row Season1; col Season 2} as well as {col Season 1 and row Season 2} in my matrix as 3.

Is there anyway for me to do this? I tried a few things but decided to give a shoutout to the community in case there is something simple out there I'm missing!

Thanks a bunch!

CodePudding user response：

There are three steps and decided to rebuild the original matrix and call it S:

# Make square matrix of zeros
rc <- length(unique(df[[1]]) ) # going to assume that number of unique values is same in both cols
S <- diag(1, rc,rc)

# Label rows and cols
dimnames(S) <- list( sort(unique(df[[1]])), sort( unique(df[[2]])) )

# Assign value to matrix positions based on values of df[[3]]

S[ data.matrix( df[1:2])  ] <-   # using 2 col matrix indexing
    df[[3]]

# -------
> S
        Season1 Season2 Season3
Season1       1       3       0
Season2       0       1       4
Season3       5       0       1

It's now a real matrix rather than a dataframe.