Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.9/dist-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._libs import lib 

11from pandas.errors import LossySetitemError 

12 

13from pandas.core.dtypes.cast import np_can_hold_element 

14from pandas.core.dtypes.common import is_numeric_dtype 

15 

16if TYPE_CHECKING: 

17 from pandas._typing import ( 

18 ArrayLike, 

19 npt, 

20 ) 

21 

22 

23def to_numpy_dtype_inference( 

24 arr: ArrayLike, dtype: npt.DTypeLike | None, na_value, hasna: bool 

25) -> tuple[npt.DTypeLike, Any]: 

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

27 dtype_given = False 

28 if hasna: 

29 if arr.dtype.kind == "b": 

30 dtype = np.dtype(np.object_) 

31 else: 

32 if arr.dtype.kind in "iu": 

33 dtype = np.dtype(np.float64) 

34 else: 

35 dtype = arr.dtype.numpy_dtype # type: ignore[union-attr] 

36 if na_value is lib.no_default: 

37 na_value = np.nan 

38 else: 

39 dtype = arr.dtype.numpy_dtype # type: ignore[union-attr] 

40 elif dtype is not None: 

41 dtype = np.dtype(dtype) 

42 dtype_given = True 

43 else: 

44 dtype_given = True 

45 

46 if na_value is lib.no_default: 

47 if dtype is None or not hasna: 

48 na_value = arr.dtype.na_value 

49 elif dtype.kind == "f": # type: ignore[union-attr] 

50 na_value = np.nan 

51 elif dtype.kind == "M": # type: ignore[union-attr] 

52 na_value = np.datetime64("nat") 

53 elif dtype.kind == "m": # type: ignore[union-attr] 

54 na_value = np.timedelta64("nat") 

55 else: 

56 na_value = arr.dtype.na_value 

57 

58 if not dtype_given and hasna: 

59 try: 

60 np_can_hold_element(dtype, na_value) # type: ignore[arg-type] 

61 except LossySetitemError: 

62 dtype = np.dtype(np.object_) 

63 return dtype, na_value