CLN: remove unused coerce arg in NDFrame._convert

pandas/core/dtypes/cast.py

@@ -1177,45 +1177,32 @@ def soft_convert_objects(
     datetime: bool = True,
     numeric: bool = True,
     timedelta: bool = True,
-    coerce: bool = False,
     copy: bool = True,
 ):
-    """ if we have an object dtype, try to coerce dates and/or numbers """
+    """
+    Try to coerce datetime, timedelta, and numeric object-dtype columns
+    to inferred dtype.
+
+    Parameters
+    ----------
+    values : np.ndarray[object]
+    datetime : bool, default True
+    numeric: bool, default True
+    timedelta : bool, default True
+    copy : bool, default True
+
+    Returns
+    -------
+    np.ndarray
+    """
     validate_bool_kwarg(datetime, "datetime")
     validate_bool_kwarg(numeric, "numeric")
     validate_bool_kwarg(timedelta, "timedelta")
-    validate_bool_kwarg(coerce, "coerce")
     validate_bool_kwarg(copy, "copy")
 
     conversion_count = sum((datetime, numeric, timedelta))
     if conversion_count == 0:
         raise ValueError("At least one of datetime, numeric or timedelta must be True.")
-    elif conversion_count > 1 and coerce:
-        raise ValueError(
-            "Only one of 'datetime', 'numeric' or "
-            "'timedelta' can be True when coerce=True."
-        )
-
-    if not is_object_dtype(values.dtype):
-        # If not object, do not attempt conversion
-        values = values.copy() if copy else values
-        return values
-
-    # If 1 flag is coerce, ensure 2 others are False
-    if coerce:
-        # Immediate return if coerce
-        if datetime:
-            from pandas import to_datetime
-
-            return to_datetime(values, errors="coerce").to_numpy()
-        elif timedelta:
-            from pandas import to_timedelta
-
-            return to_timedelta(values, errors="coerce").to_numpy()
-        elif numeric:
-            from pandas import to_numeric
-
-            return to_numeric(values, errors="coerce")
 
     # Soft conversions
     if datetime:

pandas/core/generic.py

@@ -5997,7 +5997,6 @@ def _convert(
         datetime: bool_t = False,
         numeric: bool_t = False,
         timedelta: bool_t = False,
-        coerce: bool_t = False,
     ) -> FrameOrSeries:
         """
         Attempt to infer better dtype for object columns
@@ -6011,9 +6010,6 @@ def _convert(
             unconvertible values becoming NaN.
         timedelta : bool, default False
             If True, convert to timedelta where possible.
-        coerce : bool, default False
-            If True, force conversion with unconvertible values converted to
-            nulls (NaN or NaT).
 
         Returns
         -------
@@ -6022,13 +6018,11 @@ def _convert(
         validate_bool_kwarg(datetime, "datetime")
         validate_bool_kwarg(numeric, "numeric")
         validate_bool_kwarg(timedelta, "timedelta")
-        validate_bool_kwarg(coerce, "coerce")
         return self._constructor(
             self._mgr.convert(
                 datetime=datetime,
                 numeric=numeric,
                 timedelta=timedelta,
-                coerce=coerce,
                 copy=True,
             )
         ).__finalize__(self)
@@ -6076,9 +6070,7 @@ def infer_objects(self: FrameOrSeries) -> FrameOrSeries:
         # python objects will still be converted to
         # native numpy numeric types
         return self._constructor(
-            self._mgr.convert(
-                datetime=True, numeric=False, timedelta=True, coerce=False, copy=True
-            )
+            self._mgr.convert(datetime=True, numeric=False, timedelta=True, copy=True)
         ).__finalize__(self, method="infer_objects")
 
     @final

pandas/core/internals/blocks.py

@@ -700,7 +700,6 @@ def convert(
         datetime: bool = True,
         numeric: bool = True,
         timedelta: bool = True,
-        coerce: bool = False,
     ) -> List["Block"]:
         """
         attempt to coerce any object types to better types return a copy
@@ -2506,12 +2505,12 @@ def convert(
         datetime: bool = True,
         numeric: bool = True,
         timedelta: bool = True,
-        coerce: bool = False,
     ) -> List["Block"]:
         """
-        attempt to coerce any object types to better types return a copy of
+        attempt to cast any object types to better types return a copy of
         the block (if copy = True) by definition we ARE an ObjectBlock!!!!!
         """
+
         # operate column-by-column
         def f(mask, val, idx):
             shape = val.shape
@@ -2520,7 +2519,6 @@ def f(mask, val, idx):
                 datetime=datetime,
                 numeric=numeric,
                 timedelta=timedelta,
-                coerce=coerce,
                 copy=copy,
             )
             if isinstance(values, np.ndarray):

pandas/core/internals/managers.py

@@ -636,15 +636,13 @@ def convert(
         datetime: bool = True,
         numeric: bool = True,
         timedelta: bool = True,
-        coerce: bool = False,
     ) -> "BlockManager":
         return self.apply(
             "convert",
             copy=copy,
             datetime=datetime,
             numeric=numeric,
             timedelta=timedelta,
-            coerce=coerce,
         )
 
     def replace(self, to_replace, value, inplace: bool, regex: bool) -> "BlockManager":

pandas/tests/frame/methods/test_to_csv.py

@@ -251,7 +251,7 @@ def make_dtnat_arr(n, nnat=None):
             df = DataFrame(dict(a=s1, b=s2))
             df.to_csv(pth, chunksize=chunksize)
 
-            recons = self.read_csv(pth)._convert(datetime=True, coerce=True)
+            recons = self.read_csv(pth).apply(to_datetime)
             tm.assert_frame_equal(df, recons, check_names=False)
 
     @pytest.mark.slow

pandas/tests/io/test_html.py

@@ -14,7 +14,15 @@
 from pandas.errors import ParserError
 import pandas.util._test_decorators as td
 
-from pandas import DataFrame, MultiIndex, Series, Timestamp, date_range, read_csv
+from pandas import (
+    DataFrame,
+    MultiIndex,
+    Series,
+    Timestamp,
+    date_range,
+    read_csv,
+    to_datetime,
+)
 import pandas._testing as tm
 
 from pandas.io.common import file_path_to_url
@@ -610,7 +618,7 @@ def try_remove_ws(x):
         gtnew = ground_truth.applymap(try_remove_ws)
         converted = dfnew._convert(datetime=True, numeric=True)
         date_cols = ["Closing Date", "Updated Date"]
-        converted[date_cols] = converted[date_cols]._convert(datetime=True, coerce=True)
+        converted[date_cols] = converted[date_cols].apply(to_datetime)
         tm.assert_frame_equal(converted, gtnew)
 
     @pytest.mark.slow

pandas/tests/series/methods/test_convert.py

@@ -3,45 +3,23 @@
 import numpy as np
 import pytest
 
-from pandas import NaT, Series, Timestamp
+from pandas import Series, Timestamp
 import pandas._testing as tm
 
 
 class TestConvert:
     def test_convert(self):
         # GH#10265
-        # Tests: All to nans, coerce, true
-        # Test coercion returns correct type
-        ser = Series(["a", "b", "c"])
-        results = ser._convert(datetime=True, coerce=True)
-        expected = Series([NaT] * 3)
-        tm.assert_series_equal(results, expected)
-
-        results = ser._convert(numeric=True, coerce=True)
-        expected = Series([np.nan] * 3)
-        tm.assert_series_equal(results, expected)
-
-        expected = Series([NaT] * 3, dtype=np.dtype("m8[ns]"))
-        results = ser._convert(timedelta=True, coerce=True)
-        tm.assert_series_equal(results, expected)
-
         dt = datetime(2001, 1, 1, 0, 0)
         td = dt - datetime(2000, 1, 1, 0, 0)
 
         # Test coercion with mixed types
         ser = Series(["a", "3.1415", dt, td])
-        results = ser._convert(datetime=True, coerce=True)
-        expected = Series([NaT, NaT, dt, NaT])
-        tm.assert_series_equal(results, expected)
 
-        results = ser._convert(numeric=True, coerce=True)
+        results = ser._convert(numeric=True)
         expected = Series([np.nan, 3.1415, np.nan, np.nan])
         tm.assert_series_equal(results, expected)
 
-        results = ser._convert(timedelta=True, coerce=True)
-        expected = Series([NaT, NaT, NaT, td], dtype=np.dtype("m8[ns]"))
-        tm.assert_series_equal(results, expected)
-
         # Test standard conversion returns original
         results = ser._convert(datetime=True)
         tm.assert_series_equal(results, ser)
@@ -116,19 +94,6 @@ def test_convert(self):
                 datetime(2001, 1, 3, 0, 0),
             ]
         )
-        s2 = Series(
-            [
-                datetime(2001, 1, 1, 0, 0),
-                datetime(2001, 1, 2, 0, 0),
-                datetime(2001, 1, 3, 0, 0),
-                "foo",
-                1.0,
-                1,
-                Timestamp("20010104"),
-                "20010105",
-            ],
-            dtype="O",
-        )
 
         result = ser._convert(datetime=True)
         expected = Series(
@@ -137,35 +102,12 @@ def test_convert(self):
         )
         tm.assert_series_equal(result, expected)
 
-        result = ser._convert(datetime=True, coerce=True)
-        tm.assert_series_equal(result, expected)
-
-        expected = Series(
-            [
-                Timestamp("20010101"),
-                Timestamp("20010102"),
-                Timestamp("20010103"),
-                NaT,
-                NaT,
-                NaT,
-                Timestamp("20010104"),
-                Timestamp("20010105"),
-            ],
-            dtype="M8[ns]",
-        )
-        result = s2._convert(datetime=True, numeric=False, timedelta=False, coerce=True)
-        tm.assert_series_equal(result, expected)
-        result = s2._convert(datetime=True, coerce=True)
-        tm.assert_series_equal(result, expected)
-
-        ser = Series(["foo", "bar", 1, 1.0], dtype="O")
-        result = ser._convert(datetime=True, coerce=True)
-        expected = Series([NaT] * 2 + [Timestamp(1)] * 2)
+        result = ser._convert(datetime=True)
         tm.assert_series_equal(result, expected)
 
         # preserver if non-object
         ser = Series([1], dtype="float32")
-        result = ser._convert(datetime=True, coerce=True)
+        result = ser._convert(datetime=True)
         tm.assert_series_equal(result, ser)
 
         # FIXME: dont leave commented-out
@@ -174,16 +116,6 @@ def test_convert(self):
         # result = res._convert(convert_dates=True,convert_numeric=False)
         # assert result.dtype == 'M8[ns]'
 
-        # dateutil parses some single letters into today's value as a date
-        expected = Series([NaT])
-        for x in "abcdefghijklmnopqrstuvwxyz":
-            ser = Series([x])
-            result = ser._convert(datetime=True, coerce=True)
-            tm.assert_series_equal(result, expected)
-            ser = Series([x.upper()])
-            result = ser._convert(datetime=True, coerce=True)
-            tm.assert_series_equal(result, expected)
-
     def test_convert_no_arg_error(self):
         ser = Series(["1.0", "2"])
         msg = r"At least one of datetime, numeric or timedelta must be True\."