Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.11/site-packages/pandas/core/arrays/_utils.py: 22%

1from __future__ import annotations 

2 

3from typing import ( 

4 TYPE_CHECKING, 

5 Any, 

6) 

7 

8import numpy as np 

9 

10from pandas._config import is_nan_na 

11 

12from pandas._libs import lib 

13from pandas._libs.missing import NA 

14from pandas.errors import LossySetitemError 

15 

16from pandas.core.dtypes.cast import np_can_hold_element 

17from pandas.core.dtypes.common import is_numeric_dtype 

18 

19if TYPE_CHECKING: 

20 from pandas._typing import ( 

21 npt, 

22 ) 

23 

24 from pandas.core.arrays.base import ExtensionArray 

25 

26 

27def to_numpy_dtype_inference( 

28 arr: ExtensionArray, 

29 dtype: npt.DTypeLike | None, 

30 na_value, 

31 hasna: bool, 

32) -> tuple[np.dtype | None, Any]: 

33 result_dtype: np.dtype | None 

34 inferred_numeric_dtype = False 

35 if dtype is None and is_numeric_dtype(arr.dtype): 

36 inferred_numeric_dtype = True 

37 if hasna: 

38 if arr.dtype.kind == "b": 

39 result_dtype = np.dtype(np.object_) 

40 else: 

41 if arr.dtype.kind in "iu": 

42 result_dtype = np.dtype(np.float64) 

43 else: 

44 result_dtype = arr.dtype.numpy_dtype # type: ignore[attr-defined] 

45 if na_value is lib.no_default: 

46 if not is_nan_na(): 

47 na_value = NA 

48 dtype = np.dtype(object) 

49 else: 

50 na_value = np.nan 

51 else: 

52 result_dtype = arr.dtype.numpy_dtype # type: ignore[attr-defined] 

53 elif dtype is not None: 

54 result_dtype = np.dtype(dtype) 

55 else: 

56 result_dtype = None 

57 

58 if na_value is lib.no_default: 

59 if result_dtype is None or not hasna: 

60 na_value = arr.dtype.na_value 

61 elif result_dtype.kind == "f": 

62 na_value = np.nan 

63 elif result_dtype.kind == "M": 

64 unit = np.datetime_data(result_dtype)[0] # type: ignore[arg-type] 

65 na_value = np.datetime64("NaT", unit) # type: ignore[call-overload] 

66 elif result_dtype.kind == "m": 

67 unit = np.datetime_data(result_dtype)[0] # type: ignore[arg-type] 

68 na_value = np.timedelta64("NaT", unit) # type: ignore[call-overload] 

69 else: 

70 na_value = arr.dtype.na_value 

71 

72 if inferred_numeric_dtype and hasna: 

73 try: 

74 np_can_hold_element(result_dtype, na_value) # type: ignore[arg-type] 

75 except LossySetitemError: 

76 result_dtype = np.dtype(np.object_) 

77 return result_dtype, na_value