From 7ab2a74c304c6791f8f28edc01b7f43b2cbd2fab Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Thu, 29 Nov 2018 10:16:32 -0600
Subject: [PATCH] Remove _coerce_to_dtype

---
 pandas/core/dtypes/common.py       | 32 ------------------------------
 pandas/tests/dtypes/test_dtypes.py | 15 --------------
 2 files changed, 47 deletions(-)

diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index 5a6a49360e1df..e1141c6b6b3a8 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -1767,38 +1767,6 @@ def is_complex_dtype(arr_or_dtype):
     return issubclass(tipo, np.complexfloating)
 
 
-def _coerce_to_dtype(dtype):
-    """
-    Coerce a string or np.dtype to a pandas or numpy
-    dtype if possible.
-
-    If we cannot convert to a pandas dtype initially,
-    we convert to a numpy dtype.
-
-    Parameters
-    ----------
-    dtype : The dtype that we want to coerce.
-
-    Returns
-    -------
-    pd_or_np_dtype : The coerced dtype.
-    """
-
-    if is_categorical_dtype(dtype):
-        categories = getattr(dtype, 'categories', None)
-        ordered = getattr(dtype, 'ordered', False)
-        dtype = CategoricalDtype(categories=categories, ordered=ordered)
-    elif is_datetime64tz_dtype(dtype):
-        dtype = DatetimeTZDtype.construct_from_string(dtype)
-    elif is_period_dtype(dtype):
-        dtype = PeriodDtype(dtype)
-    elif is_interval_dtype(dtype):
-        dtype = IntervalDtype(dtype)
-    else:
-        dtype = np.dtype(dtype)
-    return dtype
-
-
 def _get_dtype(arr_or_dtype):
     """
     Get the dtype instance associated with an array
diff --git a/pandas/tests/dtypes/test_dtypes.py b/pandas/tests/dtypes/test_dtypes.py
index fb9fbe0f5ee1d..888f4bdb73291 100644
--- a/pandas/tests/dtypes/test_dtypes.py
+++ b/pandas/tests/dtypes/test_dtypes.py
@@ -17,7 +17,6 @@
     is_dtype_equal, is_datetime64_ns_dtype,
     is_datetime64_dtype, is_interval_dtype,
     is_datetime64_any_dtype, is_string_dtype,
-    _coerce_to_dtype,
     is_bool_dtype,
 )
 from pandas.core.sparse.api import SparseDtype
@@ -173,12 +172,6 @@ def test_subclass(self):
         assert issubclass(type(a), type(a))
         assert issubclass(type(a), type(b))
 
-    def test_coerce_to_dtype(self):
-        assert (_coerce_to_dtype('datetime64[ns, US/Eastern]') ==
-                DatetimeTZDtype('ns', 'US/Eastern'))
-        assert (_coerce_to_dtype('datetime64[ns, Asia/Tokyo]') ==
-                DatetimeTZDtype('ns', 'Asia/Tokyo'))
-
     def test_compat(self):
         assert is_datetime64tz_dtype(self.dtype)
         assert is_datetime64tz_dtype('datetime64[ns, US/Eastern]')
@@ -319,10 +312,6 @@ def test_identity(self):
         assert PeriodDtype('period[1S1U]') == PeriodDtype('period[1000001U]')
         assert PeriodDtype('period[1S1U]') is PeriodDtype('period[1000001U]')
 
-    def test_coerce_to_dtype(self):
-        assert _coerce_to_dtype('period[D]') == PeriodDtype('period[D]')
-        assert _coerce_to_dtype('period[3M]') == PeriodDtype('period[3M]')
-
     def test_compat(self):
         assert not is_datetime64_ns_dtype(self.dtype)
         assert not is_datetime64_ns_dtype('period[D]')
@@ -517,10 +506,6 @@ def test_is_dtype(self):
         assert not IntervalDtype.is_dtype(np.int64)
         assert not IntervalDtype.is_dtype(np.float64)
 
-    def test_coerce_to_dtype(self):
-        assert (_coerce_to_dtype('interval[int64]') ==
-                IntervalDtype('interval[int64]'))
-
     def test_equality(self):
         assert is_dtype_equal(self.dtype, 'interval[int64]')
         assert is_dtype_equal(self.dtype, IntervalDtype('int64'))