fix(auto-fixer): fix chained groupby(level=N).groupby('date') pattern

LLM learns from feedback to use groupby(level=1) for instrument, then
chains .groupby('date') to add the date dimension — but DataFrameGroupBy
has no .groupby() method, causing AttributeError at runtime.

Replace the invalid chain with a correct two-level groupby using
index.get_level_values(), consistent with the existing instrument+date fix.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
TPTBusiness
2026-04-26 15:34:10 +02:00
parent f4deda99b5
commit 8aec974702
2 changed files with 48 additions and 1 deletions
+15
View File
@@ -58,6 +58,21 @@ class TestGroupbyColumnOnMultiindex:
assert "groupby('instrument')" in result
class TestChainedGroupby:
def test_chained_groupby_level_then_date(self, fixer):
code = "df.groupby(level=1).groupby('date')['price_volume'].transform('cumsum')"
result = fixer.fix(code)
assert "get_level_values(1)" in result
assert "get_level_values(0).normalize()" in result
assert ".groupby('date')" not in result
def test_chained_groupby_with_double_quotes(self, fixer):
code = 'df.groupby(level=0).groupby("date")["col"].sum()'
result = fixer.fix(code)
assert "get_level_values" in result
assert '.groupby("date")' not in result
class TestRollingDdof:
def test_removes_ddof_from_rolling_args(self, fixer):
result = fixer.fix("df.rolling(20, min_periods=1, ddof=1).std()")