|
99 | 99 | from pandas import Series
|
100 | 100 | from pandas.core.arrays import ExtensionArray
|
101 | 101 | from pandas.core.indexes.base import Index
|
102 |
| - from pandas.core.indexes.datetimes import DatetimeIndex |
103 | 102 |
|
104 | 103 | _int8_max = np.iinfo(np.int8).max
|
105 | 104 | _int16_max = np.iinfo(np.int16).max
|
@@ -1121,57 +1120,6 @@ def astype_nansafe(
|
1121 | 1120 | return arr.view(dtype)
|
1122 | 1121 |
|
1123 | 1122 |
|
1124 |
| -def maybe_convert_objects( |
1125 |
| - values: np.ndarray, convert_numeric: bool = True |
1126 |
| -) -> Union[np.ndarray, "DatetimeIndex"]: |
1127 |
| - """ |
1128 |
| - If we have an object dtype array, try to coerce dates and/or numbers. |
1129 |
| -
|
1130 |
| - Parameters |
1131 |
| - ---------- |
1132 |
| - values : ndarray |
1133 |
| - convert_numeric : bool, default True |
1134 |
| -
|
1135 |
| - Returns |
1136 |
| - ------- |
1137 |
| - ndarray or DatetimeIndex |
1138 |
| - """ |
1139 |
| - validate_bool_kwarg(convert_numeric, "convert_numeric") |
1140 |
| - |
1141 |
| - orig_values = values |
1142 |
| - |
1143 |
| - # convert dates |
1144 |
| - if is_object_dtype(values.dtype): |
1145 |
| - values = lib.maybe_convert_objects(values, convert_datetime=True) |
1146 |
| - |
1147 |
| - # convert timedeltas |
1148 |
| - if is_object_dtype(values.dtype): |
1149 |
| - values = lib.maybe_convert_objects(values, convert_timedelta=True) |
1150 |
| - |
1151 |
| - # convert to numeric |
1152 |
| - if is_object_dtype(values.dtype): |
1153 |
| - if convert_numeric: |
1154 |
| - try: |
1155 |
| - new_values = lib.maybe_convert_numeric( |
1156 |
| - values, set(), coerce_numeric=True |
1157 |
| - ) |
1158 |
| - except (ValueError, TypeError): |
1159 |
| - pass |
1160 |
| - else: |
1161 |
| - # if we are all nans then leave me alone |
1162 |
| - if not isna(new_values).all(): |
1163 |
| - values = new_values |
1164 |
| - |
1165 |
| - else: |
1166 |
| - # soft-conversion |
1167 |
| - values = lib.maybe_convert_objects(values) |
1168 |
| - |
1169 |
| - if values is orig_values: |
1170 |
| - values = values.copy() |
1171 |
| - |
1172 |
| - return values |
1173 |
| - |
1174 |
| - |
1175 | 1123 | def soft_convert_objects(
|
1176 | 1124 | values: np.ndarray,
|
1177 | 1125 | datetime: bool = True,
|
|
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