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Replace with nested dict raises for overlapping keys #27696

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Merged
merged 10 commits into from
Aug 27, 2019
Merged

Replace with nested dict raises for overlapping keys #27696

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7e461a1
remove \n from docstring
charlesdong1991 Dec 3, 2018
1314059
fix conflicts
charlesdong1991 Jan 19, 2019
8bcb313
Merge remote-tracking branch 'upstream/master'
charlesdong1991 Jul 30, 2019
4f4f293
Fix boolean error in replace
charlesdong1991 Aug 1, 2019
7529084
tst
charlesdong1991 Aug 5, 2019
2c6d5f6
Merge remote-tracking branch 'upstream/master' into fix_issue_27660
charlesdong1991 Aug 24, 2019
eb6cee8
code change based on review
charlesdong1991 Aug 24, 2019
18bd517
code change based on review
charlesdong1991 Aug 25, 2019
20ae4f4
fix conflict
charlesdong1991 Aug 27, 2019
2c97495
minor naming change
charlesdong1991 Aug 27, 2019
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6 changes: 5 additions & 1 deletion pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6640,7 +6640,11 @@ def replace(

for k, v in items:
keys, values = list(zip(*v.items())) or ([], [])
if set(keys) & set(values):
# add another check to avoid boolean being regarded
# as binary in python set
if set(keys) & set(values) and set(map(str, keys)) & set(
map(str, values)
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I think this might be a little bit too permissive now, as it will allow {0: 1.0, 1: 'a'}, which was previously rejected (might not actually matter but is a change in behavior we should be cognizant of).

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yeah, i should have thought of it more thoroughly

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Can this just not be removed altogether? Not clear on the purpose of it

):
raise ValueError(
"Replacement not allowed with "
"overlapping keys and values"
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12 changes: 12 additions & 0 deletions pandas/tests/generic/test_generic.py
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Expand Up @@ -948,3 +948,15 @@ def test_deprecated_get_dtype_counts(self):
df = DataFrame([1])
with tm.assert_produces_warning(FutureWarning):
df.get_dtype_counts()

def test_boolean_in_replace(self):
# GH 27660
df = DataFrame({"col": [False, True, 0, 1]})

result = df.replace({"col": {False: 0, True: 1}})
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If you were to switch the replacement to {False: 1, True: 0} then this test will fail as the integers will get incorrectly replaced:

In [2]: df = pd.DataFrame({'col': [False, True, 0, 1]})

In [3]: df.replace({'col': {False: 1, True: 0}})
Out[3]: 
   col
0    1
1    0
2    1
3    0

I think the current version of the test is passing because 0/1 are just getting replaced by themselves.

This is a consequence of how Python handles hashing, specifically 0/False have the same hash and evaluate equally with == (Python's fallback on hash collision), so they'll be considered the same in set operations or when looking up keys in a dict (likewise for 1/True).

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ehh, you are very right, it's not good solution @jschendel

expected = DataFrame({"col": [0, 1, 0, 1]})
assert_frame_equal(result, expected)

msg = "Replacement not allowed with overlapping keys and values"
with pytest.raises(ValueError, match=msg):
df.replace({"col": {0: 1, 1: "a"}})