DataFrames, get a subset in which the value of a particular column is not missing

General Usage
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1

I’m probably doing something dumb here, but I have a DataFrame and I want to get all rows for which a particular column (which is called :Level and is type Union{Int, Missing}) is not missing. My first two tries (using DataFramesMeta.jl) haven’t worked:

julia> standards = @subset(df, filter(x->true,skipmissing(:Level)))
ERROR: ArgumentError: length 10 of vector returned from function #478 is different from number of rows 20 of the source data frame.
# Long stacktrace that doesn't seem relevant here

julia> standards = @subset(df, !.(ismissing.(:Level)))
ERROR: syntax: invalid identifier name "."
Stacktrace:
 [1] top-level scope
   @ none:1

What am I missing (pun intended)?

2

You can do @rsubset for row-wise operatoins

julia> using DataFramesMeta

julia> df = DataFrame(Level = [1, 2, missing, 4]);

julia> @rsubset df !ismissing(:Level)
3×1 DataFrame
 Row │ Level  
     │ Int64? 
─────┼────────
   1 │      1
   2 │      2
   3 │      4

The first one errors because the returned value from a @subset operation has to be a boolean vector of the same length as the original data frame.

In the second one, you have problems with the broadcasting syntax, try

julia> @subset df (!).(ismissing.(:Level))
3×1 DataFrame
 Row │ Level  
     │ Int64? 
─────┼────────
   1 │      1
   2 │      2
   3 │      4
3

another option is just:

subdf = df[.! ismissing.(df.Level),:]

4

All of these work. Thanks to both! I think I’ll mark pdeffebach’s answer because it’s first. Thanks again!