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BUG: Cleaner exception when .iloc called with non-integer list #25759

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Merged
merged 11 commits into from
Mar 26, 2019
Merged

BUG: Cleaner exception when .iloc called with non-integer list #25759

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f865b72
better error message for iloc called with non-integer keys
Mar 18, 2019
1861a1a
updated whatsnew
Mar 18, 2019
4cb4667
change from np.int -> np.numeric
Mar 18, 2019
0b00f3e
added tests for new exception
Mar 18, 2019
6d94f4a
revise parameterized tests
Mar 18, 2019
1f0302f
modified whatsnew
Mar 19, 2019
3659f04
clarify commenting around key checks
Mar 19, 2019
317f9bf
update tests to match new exception
Mar 19, 2019
867a71e
Merge branch 'master' of https://github.com/pandas-dev/pandas into lo…
Mar 19, 2019
f816fd9
change to is_numeric_dtype
Mar 19, 2019
a8caad0
alphabetize imports
Mar 19, 2019
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -204,7 +204,7 @@ Interval
Indexing
^^^^^^^^

-
- Added an exception message when calling :meth:`DataFrame.iloc` with a list of non-numeric objects.
-
-

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4 changes: 4 additions & 0 deletions pandas/core/indexing.py
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Expand Up @@ -2079,6 +2079,10 @@ def _validate_key(self, key, axis):
arr = np.array(key)
len_axis = len(self.obj._get_axis(axis))

if not np.issubdtype(arr.dtype, np.number):
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use is_integer_dtype

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@kykosic kykosic Mar 19, 2019 •
edited
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This will cause a new exception when an array of float values is passed to .iloc. Currently float values are allowed and the array is cast to integer dtype. This will cause some regression.

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then you need to thread this in the appropriate place

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alt you could check is_numeric_dtype

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Alright I tried to reorganize it a bit, let me know if I misunderstood what you meant.

raise IndexError(".iloc requires integer indexers, got "
"{arr}".format(arr=arr))

if len(arr) and (arr.max() >= len_axis or arr.min() < -len_axis):
raise IndexError("positional indexers are out-of-bounds")
else:
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34 changes: 34 additions & 0 deletions pandas/tests/indexing/test_iloc.py
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Expand Up @@ -118,6 +118,40 @@ def check(result, expected):
with pytest.raises(IndexError, match=msg):
dfl.iloc[:, 4]

def test_iloc_non_integer(self):

# iloc should throw IndexError if non-numeric list is passed
df = DataFrame(np.random.random_sample((20, 5)), columns=list('ABCDE'))

msg = '.iloc requires integer indexers, got'
with pytest.raises(IndexError, match=msg):
df.iloc[:, ['A', 'D']]
with pytest.raises(IndexError, match=msg):
df.iloc[['1', '2'], :]
with pytest.raises(IndexError, match=msg):
df.iloc[[pd.datetime(2019, 1, 1)], :]

# Numeric or booleans should not raise errors
result = df.iloc[:, [0, 1]]
expected = df.loc[:, ['A', 'B']]
tm.assert_frame_equal(result, expected)

result = df.iloc[[0, 1], [0, 1, 3]]
expected = df.loc[[0, 1], ['A', 'B', 'D']]
tm.assert_frame_equal(result, expected)

result = df.iloc[:, [True, False, False, True]]
expected = df.loc[:, ['A', 'D']]
tm.assert_frame_equal(result, expected)

result = df.iloc[:, [0, 0.5]]
expected = df.loc[:, ['A', 'A']]
tm.assert_frame_equal(result, expected)

result = df.iloc[[True, False, True], :]
expected = df.loc[[0, 2], :]
tm.assert_frame_equal(result, expected)

def test_iloc_getitem_int(self):

# integer
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