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Implement check for groupby slicing and aggregation patterns. #54

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Pending determination of acceptable use cases for this pattern, this PR checks for explicit use of the following patterns with explicit slicing syntax on the groupby() method:

df.groupby(A)[B]          # for ast.Subscript nodes
df.groupby(A)[B].agg(C)   # for ast.Call nodes

Note that this requires two separate check functions due to above distinction in AST. Also, includes check to distinguish between method (node.func.attr) vs. function (node.func.id).

The implementation does not check syntax for functions, although commented tests are included in test_PD014.py in case this is determined to be acceptable syntax for check.

Closes #24 (pending)

simchuck added 5 commits March 8, 2019 15:26
Add check to distinguish method vs. function.

Also, due to structure of AST, need to treat chained aggregation method
separately from sliced method, i.e.,

    df.groupby()[]          # visitor node is ast.Subscript
    df.groupby()[].agg()    # visitor node is ast.Call
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deppen8 commented Aug 4, 2019

@simchuck, any interest in revisiting this? Once the off-by-default framework (#69) is merged, I think this would be a good PD902. It is probably too opinionated for most everyday pandas applications.

Let me know if you want to take it on. If not, I'll give it a shot.

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simchuck commented Aug 7, 2019 via email

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Check for .groupby aggregation patterns
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