STYLE: dont' use pd.api.types anywhere in tests
example here: https://github.com/pandas-dev/pandas/pull/37367/files#diff-69c698518ca64a05f8b137ff9bb5445ce9fd21139b396e9b0d4ce7338b2a3984R132

we should just ban this with a precommit style rule (and import things directly). the doc-strings also should be updated to do the import once.

```
grep -r pd.api.types ~/pandas-dev/pandas
/home/jreback/pandas-dev/pandas/_libs/lib.pyx:    >>> pd.api.types.is_scalar(dt)
/home/jreback/pandas-dev/pandas/_libs/lib.pyx:    >>> pd.api.types.is_scalar([2, 3])
/home/jreback/pandas-dev/pandas/_libs/lib.pyx:    >>> pd.api.types.is_scalar({0: 1, 2: 3})
/home/jreback/pandas-dev/pandas/_libs/lib.pyx:    >>> pd.api.types.is_scalar((0, 2))
/home/jreback/pandas-dev/pandas/_libs/lib.pyx:    >>> pd.api.types.is_scalar(Fraction(3, 5))
/home/jreback/pandas-dev/pandas/tests/frame/test_ufunc.py:    if pd.api.types.is_extension_array_dtype(dtype) or isinstance(dtype, dict):
/home/jreback/pandas-dev/pandas/tests/frame/test_ufunc.py:        pd.api.types.is_extension_array_dtype(dtype_a)
/home/jreback/pandas-dev/pandas/tests/frame/test_ufunc.py:        or pd.api.types.is_extension_array_dtype(dtype_b)
/home/jreback/pandas-dev/pandas/tests/frame/test_ufunc.py:    if pd.api.types.is_extension_array_dtype(dtype) or isinstance(dtype, dict):
/home/jreback/pandas-dev/pandas/tests/extension/base/dtype.py:        return not pd.api.types.is_string_dtype(dtype)
/home/jreback/pandas-dev/pandas/tests/extension/base/dtype.py:        return not pd.api.types.is_object_dtype(dtype)
/home/jreback/pandas-dev/pandas/tests/extension/arrow/arrays.py:        if pd.api.types.is_scalar(item):
/home/jreback/pandas-dev/pandas/tests/extension/arrow/test_bool.py:    assert pd.api.types.is_bool_dtype(data)
/home/jreback/pandas-dev/pandas/tests/extension/json/array.py:            if pd.api.types.is_bool_dtype(item.dtype):
/home/jreback/pandas-dev/pandas/tests/extension/decimal/array.py:        if pd.api.types.is_list_like(value):
/home/jreback/pandas-dev/pandas/tests/extension/decimal/array.py:            if pd.api.types.is_scalar(key):
/home/jreback/pandas-dev/pandas/tests/extension/list/array.py:        elif pd.api.types.is_string_dtype(dtype) and not pd.api.types.is_object_dtype(
/home/jreback/pandas-dev/pandas/tests/extension/test_integer.py:                and pd.api.types.is_integer_dtype(other.dtype)
/home/jreback/pandas-dev/pandas/tests/extension/test_floating.py:                and pd.api.types.is_float_dtype(other.dtype)
/home/jreback/pandas-dev/pandas/core/dtypes/inference.py:    >>> pd.api.types.is_number(1)
/home/jreback/pandas-dev/pandas/core/dtypes/inference.py:    >>> pd.api.types.is_number(7.15)
/home/jreback/pandas-dev/pandas/core/dtypes/inference.py:    >>> pd.api.types.is_number(False)
/home/jreback/pandas-dev/pandas/core/dtypes/inference.py:    >>> pd.api.types.is_number("foo")
/home/jreback/pandas-dev/pandas/core/dtypes/inference.py:    >>> pd.api.types.is_number("5")
/home/jreback/pandas-dev/pandas/core/generic.py:        >>> cat_dtype = pd.api.types.CategoricalDtype(
```