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Interpolation nonnumeric error handling #21773

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4 changes: 4 additions & 0 deletions doc/source/whatsnew/v0.24.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -243,6 +243,10 @@ Documentation Changes
Bug Fixes
~~~~~~~~~

**Data-type specific**

- Bug in :meth:`Series.interpolate()` where appropiate error was not raised when interpolating with a non-numeric index column (:issue:`21662`)

Categorical
^^^^^^^^^^^

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7 changes: 7 additions & 0 deletions pandas/core/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -6024,6 +6024,13 @@ def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
raise NotImplementedError("Interpolation with NaNs in the index "
"has not been implemented. Try filling "
"those NaNs before interpolating.")

if not np.issubdtype(index.dtype, np.number):
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use is_numeric_dtype intead

raise TypeError("Index column must be numeric when using any "
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this should be a ValueError

"interpolation method other than linear. Try "
"setting a numeric index column before "
"interpolating")

data = _maybe_transposed_self._data
new_data = data.interpolate(method=method, axis=ax, index=index,
values=_maybe_transposed_self, limit=limit,
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13 changes: 13 additions & 0 deletions pandas/tests/generic/test_generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -1008,3 +1008,16 @@ def test_pipe_panel(self):

with pytest.raises(ValueError):
result = wp.pipe((f, 'y'), x=1, y=1)

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this needs to go in pandas/tests/series/test_missing.py

also some tests are failing

def test_interpolate(self):
# Using a numeric index column
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can you add the issue number here

df = DataFrame([0, 1, np.nan, 3], index=[1, 2, 3, 4])
series = Series(df[0])
assert series.interpolate(
method="quadratic").equals(series.interpolate(method="linear"))

# Using a non-numeric index column
df = DataFrame([0, 1, np.nan, 3], index=["A", "B", "C", "D"])
series = Series(df[0])
with pytest.raises(TypeError):
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check the returned message here

result = series.interpolate(method="quadratic")