Clarification / Question: Dataframe.filter AND/OR mask?

[drowzy]

I see in the docs that one can filter using a mask:

df = Explorer.DataFrame.from_map(%{a: ["a", "b", "c"], b: [1, 2, 3]})
Explorer.DataFrame.filter(df, Explorer.Series.greater(df["b"], 1))

#Explorer.DataFrame<
[rows: 2, columns: 2]
a string ["b", "c"]
b integer [2, 3]
>

How does one create an AND/OR mask? I could compute them manually and use a list, but is there a better way?
Sort of what I'm looking for:

df = Explorer.DataFrame.from_map(%{a: ["a", "b", "c"], b: [1, 2, 3]})
mask = Explorer.Series.or(Explorer.Series.equal(df["b"], 1), Explorer.Series.equal(df["b"], 3))

Explorer.DataFrame.filter(df, mask)

#Explorer.DataFrame<
[rows: 2, columns: 2]
a string ["b", "c"]
b integer [1, 3]
>

[cigrainger]

There's not anything built in right now, but I think something like this is a great idea. I think polars has something for this. I'll look into it, but would also be happy to accept a PR. :)

[drowzy]

Sure! I'll submit a PR :)