DataFrames: How to remove rows containing NaNs when there are also missings

General Usage
2

The simplest is probably:

filter(row -> all(x -> !(x isa Number && isnan(x)), row), df)

You can also write:

subset(df, (names(df) .=> ByRow(x -> !(x isa Number && isnan(x))))...)

Note that names(df, Union{Float64, Missing}) is not fully correct, as your column could have e.g. Any type and still contain NaN.

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