Implement Series.where #922
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## master #922 +/- ##
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+ Coverage 94.52% 94.53% +<.01%
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Files 34 34
Lines 6465 6476 +11
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+ Hits 6111 6122 +11
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ueshin
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Shall we add more tests in test_series to check various patterns? e.g.,
>>> s1 = pd.Series([0, 1, 2, 3, 4])
>>> s2 = pd.Series([100, 200, 300, 400, 500])
>>> s1.where(s2 > 100)
0 NaN
1 1.0
2 2.0
3 3.0
4 4.0
dtype: float64and negative cases?
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| return self._with_new_scol(current) | ||
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| def where(self, cond, other=np.nan): |
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@itholic seems like pandas shares the same implementation internally. After this PR is merged, can you move this into _Frame class and implement DataFrame.where as well?
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okay, i'm going to work right after this PR is merged
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Seems fine to me otherwise. |
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| # +-----------------+---+----------------+-----------------+ | ||
| data_col_name = self._internal.column_name_for(self._internal.column_index[0]) | ||
| index_column = self._internal.index_columns[0] |
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@itholic, I think this doesn't support multi-level index cases. Can you fix this please?
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index_columns can be multiple and we cannot just use the first one only.
| set_option("compute.ops_on_diff_frames", True) | ||
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| @classmethod | ||
| def tearDownClass(cls): |
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@itholic disable this. compute.ops_on_diff_frames is disabled by default because it costs a lot. We should move the test cases into OpsOnDiffFramesEnabledTest
| kser.drop_duplicates().sort_values()) | ||
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| def test_where(self): | ||
| pser1 = pd.Series([0, 1, 2, 3, 4], name=0) |
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Can you add a test when compute.ops_on_diff_frames is off? I think we can still use a scalar values for other such as int.
5 participants
Like pandas Series.where (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.where.html)
implemented function
wherefor series.