Hi all,

I would like to know how one might partition unique string values from one column of the DataFrame (C) to achieve my goal.

```
using Random, DataFrames
C = DataFrame(Team = ["Packers", "Knights", "Bills", "Falcons", "Ravens", "Chiefs", "Titans", "Rams", "Bengals", "Colts", "49ers", "Giants", "Lions", "Steelers", "Jaguars", "Dolphins", "Vikings", "Eagles", "Bears", "Jets", "Cardinals", "Patriots", "Bucs", "Cowboys", "Panthers", "Chargers", "Seahawks", "Browns"], Opponent = ["Bears", "Eagles", "Jets", "Vikings", "Dolphins", "Jaguars", "Browns", "Panthers", "Seahawks", "Chargers", "Bucs", "Cowboys", "Cardinals", "Patriots", "Chiefs", "Ravens", "Falcons", "Knights", "Packers", "Bills", "Lions", "Steelers", "49ers", "Giants", "Rams", "Colts", "Bengals", "Titans"])
```

I would like to divide C into two 1-dimensional arrays A and B such that A contains half of the entries from the column â€śTeamâ€ť, and B contains the â€śOpponentâ€ť entry from the same row (in order) as A. So A could be:

```
A = "Bills", "Ravens", "Giants", ...
```

to which the corresponding B would be:

```
B = "Jets", "Dolphins", "Cowboys", ...
```

The critical points are that all the entries in A and B are unique and correspond to the same row from the original dataframe C. The final order of entries in A and B does not matter.

Iâ€™ve tried:

```
teams = C[!, :Team]
A = sample(1:(length(teams)/2), Int(length(teams)/2), replace = false)
A = teams[A]
B = setdiff(1:(length(teams)/2), A)
B = teams[B, :]
```

But this fails to maintain the correct pairing between the rows from the â€śTeamâ€ť and â€śOpponentâ€ť columns of C. Any insightful input into my dilemma would be much appreciated. Thank you for your time!