(values, expected=None, mask=None,
type=None)
| 142 | |
| 143 | |
| 144 | def _check_array_roundtrip(values, expected=None, mask=None, |
| 145 | type=None): |
| 146 | arr = pa.array(values, from_pandas=True, mask=mask, type=type) |
| 147 | result = arr.to_pandas() |
| 148 | |
| 149 | values_nulls = pd.isnull(values) |
| 150 | if mask is None: |
| 151 | assert arr.null_count == values_nulls.sum() |
| 152 | else: |
| 153 | assert arr.null_count == (mask | values_nulls).sum() |
| 154 | |
| 155 | if expected is None: |
| 156 | if mask is None: |
| 157 | expected = pd.Series(values) |
| 158 | else: |
| 159 | expected = pd.Series(values).copy() |
| 160 | expected[mask.copy()] = None |
| 161 | |
| 162 | if expected.dtype == 'object': |
| 163 | expected = expected.replace({np.nan: None}) |
| 164 | |
| 165 | tm.assert_series_equal(pd.Series(result), expected, check_names=False) |
| 166 | |
| 167 | |
| 168 | def _check_array_from_pandas_roundtrip(np_array, type=None): |
no test coverage detected