Leftjoin changes the type of my dataframe columns from Float64 to Float64?

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1

I have a dataframe where the output is this:
Row │ TeamName OffTOPct OffRPct OffFTRate
│ String31 Float64 Float64 Float64
─────┼─────────────────────────────────────────────────
1 │ Abilene Christian 17.6662 27.9271 39.2743
2 │ Air Force 21.4742 19.5677 26.7919
3 │ Akron 17.8053 28.9216 39.3029

I run this code,
leftjoin!(SummaryPre22, Off22, on=:TeamName, makeunique=true)

to join it with a df that looks like this
Row │ TeamName Conf Tempo OE AdjOE DE AdjDE AdjEM
│ String31 String7 Float64 Float64 Float64 Float64 Float64 Float64
─────┼─────────────────────────────────────────────────────────────────────────────────────────
1 │ Abilene Christian WAC 70.9837 101.622 102.991 95.5159 99.3582 3.6328

But I get a df in return with Float64? as my column types in return.
Row │ TeamName Conf Tempo OE AdjOE DE AdjDE AdjEM OffTOPct OffRPct OffFTRate DefTOPct DefRPct DefFTRate Off2Pct Off3Pct OffFTPct Bl ⋯
│ String31 String7 Float64 Float64 Float64 Float64 Float64 Float64 Float64? Float64? Float64? Float64? Float64? Float64? Float64? Float64? Float64? Fl ⋯
─────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ Abilene Christian WAC 70.9837 101.622 102.991 95.5159 99.3582 3.6328 17.6662 27.9271 39.2743 27.8848 30.9184 49.1228 48.4087 32.2059 74.8641

This gives me an error later on:ERROR: LoadError: ArgumentError: column(s) OffTOPct and OffRPct are missing from argument(s) 2, 3, 4 and 5

I’m guessing it’s because of the type of those columns as Float64. I was wondering if anyone knew why joining the data frames would change the type like that?

2

The reason is that it is not guaranteed that for all keys in left table there are matching keys in right table.

To remove Missing union use the disallowmissing! function after join.