TST/STYLE: concatenate string literals post black reformatting

pandas/tests/arithmetic/test_numeric.py

@@ -469,7 +469,7 @@ class TestMultiplicationDivision:
             pytest.param(
                 pd.Index,
                 marks=pytest.mark.xfail(
-                    reason="Index.__div__ always " "raises", raises=TypeError
+                    reason="Index.__div__ always raises", raises=TypeError
                 ),
             ),
             pd.Series,

pandas/tests/arithmetic/test_period.py

@@ -960,7 +960,7 @@ def test_add_iadd_timedeltalike_annual(self):
     def test_pi_add_sub_timedeltalike_freq_mismatch_annual(self, mismatched_freq):
         other = mismatched_freq
         rng = pd.period_range("2014", "2024", freq="A")
-        msg = "Input has different freq(=.+)? " "from Period.*?\\(freq=A-DEC\\)"
+        msg = "Input has different freq(=.+)? from Period.*?\\(freq=A-DEC\\)"
         with pytest.raises(IncompatibleFrequency, match=msg):
             rng + other
         with pytest.raises(IncompatibleFrequency, match=msg):

pandas/tests/arithmetic/test_timedelta64.py

@@ -318,19 +318,19 @@ def _check(result, expected):
         _check(result, expected)
 
         # tz mismatches
-        msg = "Timestamp subtraction must have the same timezones or no" " timezones"
+        msg = "Timestamp subtraction must have the same timezones or no timezones"
         with pytest.raises(TypeError, match=msg):
             dt_tz - ts
         msg = "can't subtract offset-naive and offset-aware datetimes"
         with pytest.raises(TypeError, match=msg):
             dt_tz - dt
-        msg = "Timestamp subtraction must have the same timezones or no" " timezones"
+        msg = "Timestamp subtraction must have the same timezones or no timezones"
         with pytest.raises(TypeError, match=msg):
             dt_tz - ts_tz2
         msg = "can't subtract offset-naive and offset-aware datetimes"
         with pytest.raises(TypeError, match=msg):
             dt - dt_tz
-        msg = "Timestamp subtraction must have the same timezones or no" " timezones"
+        msg = "Timestamp subtraction must have the same timezones or no timezones"
         with pytest.raises(TypeError, match=msg):
             ts - dt_tz
         with pytest.raises(TypeError, match=msg):
@@ -1771,7 +1771,7 @@ def test_td64arr_floordiv_int(self, box_with_array):
         result = idx // 1
         tm.assert_equal(result, idx)
 
-        pattern = "floor_divide cannot use operands|" "Cannot divide int by Timedelta*"
+        pattern = "floor_divide cannot use operands|Cannot divide int by Timedelta*"
         with pytest.raises(TypeError, match=pattern):
             1 // idx
 

pandas/tests/arrays/categorical/test_operators.py

@@ -313,7 +313,7 @@ def test_unordered_different_categories_raises(self):
         c1 = Categorical(["a", "b"], categories=["a", "b"], ordered=False)
         c2 = Categorical(["a", "c"], categories=["c", "a"], ordered=False)
 
-        with pytest.raises(TypeError, match=("Categoricals can " "only be compared")):
+        with pytest.raises(TypeError, match=("Categoricals can only be compared")):
             c1 == c2
 
     def test_compare_different_lengths(self):

pandas/tests/arrays/test_integer.py

@@ -88,7 +88,7 @@ def test_repr_dtype(dtype, expected):
 
 def test_repr_array():
     result = repr(integer_array([1, None, 3]))
-    expected = "<IntegerArray>\n" "[1, NaN, 3]\n" "Length: 3, dtype: Int64"
+    expected = "<IntegerArray>\n[1, NaN, 3]\nLength: 3, dtype: Int64"
     assert result == expected
 
 

pandas/tests/arrays/test_period.py

@@ -259,7 +259,7 @@ def test_repr_small():
     arr = period_array(["2000", "2001"], freq="D")
     result = str(arr)
     expected = (
-        "<PeriodArray>\n" "['2000-01-01', '2001-01-01']\n" "Length: 2, dtype: period[D]"
+        "<PeriodArray>\n['2000-01-01', '2001-01-01']\nLength: 2, dtype: period[D]"
     )
     assert result == expected
 

pandas/tests/computation/test_eval.py

@@ -92,7 +92,7 @@ def _eval_single_bin(lhs, cmp1, rhs, engine):
             return c(lhs, rhs)
         except ValueError as e:
             if str(e).startswith(
-                "negative number cannot be " "raised to a fractional power"
+                "negative number cannot be raised to a fractional power"
             ):
                 return np.nan
             raise
@@ -362,7 +362,7 @@ def get_expected_pow_result(self, lhs, rhs):
             expected = _eval_single_bin(lhs, "**", rhs, self.engine)
         except ValueError as e:
             if str(e).startswith(
-                "negative number cannot be " "raised to a fractional power"
+                "negative number cannot be raised to a fractional power"
             ):
                 if self.engine == "python":
                     pytest.skip(str(e))
@@ -1944,7 +1944,7 @@ def test_empty_string_raises(engine, parser):
 
 
 def test_more_than_one_expression_raises(engine, parser):
-    with pytest.raises(SyntaxError, match=("only a single expression " "is allowed")):
+    with pytest.raises(SyntaxError, match=("only a single expression is allowed")):
         pd.eval("1 + 1; 2 + 2", engine=engine, parser=parser)
 
 

pandas/tests/extension/arrow/bool.py

@@ -33,7 +33,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from " "'{}'".format(cls, string))
+            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
 
     @classmethod
     def construct_array_type(cls):

pandas/tests/extension/decimal/array.py

@@ -40,7 +40,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from " "'{}'".format(cls, string))
+            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
 
     @property
     def _is_numeric(self):
@@ -172,7 +172,7 @@ def _reduce(self, name, skipna=True, **kwargs):
             op = getattr(self.data, name)
         except AttributeError:
             raise NotImplementedError(
-                "decimal does not support " "the {} operation".format(name)
+                "decimal does not support the {} operation".format(name)
             )
         return op(axis=0)
 

pandas/tests/extension/decimal/test_decimal.py

@@ -207,7 +207,7 @@ def test_series_repr(self, data):
 # TODO(extension)
 @pytest.mark.xfail(
     reason=(
-        "raising AssertionError as this is not implemented, " "though easy enough to do"
+        "raising AssertionError as this is not implemented, though easy enough to do"
     )
 )
 def test_series_constructor_coerce_data_to_extension_dtype_raises():

pandas/tests/extension/json/array.py

@@ -44,7 +44,7 @@ def construct_from_string(cls, string):
         if string == cls.name:
             return cls()
         else:
-            raise TypeError("Cannot construct a '{}' from " "'{}'".format(cls, string))
+            raise TypeError("Cannot construct a '{}' from '{}'".format(cls, string))
 
 
 class JSONArray(ExtensionArray):

pandas/tests/frame/test_alter_axes.py

@@ -1304,7 +1304,7 @@ def test_rename_axis_style_raises(self):
         df = DataFrame({"A": [1, 2], "B": [1, 2]}, index=["0", "1"])
 
         # Named target and axis
-        over_spec_msg = "Cannot specify both 'axis' and " "any of 'index' or 'columns'"
+        over_spec_msg = "Cannot specify both 'axis' and any of 'index' or 'columns'"
         with pytest.raises(TypeError, match=over_spec_msg):
             df.rename(index=str.lower, axis=1)
 

pandas/tests/frame/test_analytics.py

@@ -363,9 +363,7 @@ def test_corr_cov_independent_index_column(self):
     def test_corr_invalid_method(self):
         # GH 22298
         df = pd.DataFrame(np.random.normal(size=(10, 2)))
-        msg = (
-            "method must be either 'pearson', " "'spearman', 'kendall', or a callable, "
-        )
+        msg = "method must be either 'pearson', 'spearman', 'kendall', or a callable, "
         with pytest.raises(ValueError, match=msg):
             df.corr(method="____")
 
@@ -1441,7 +1439,7 @@ def test_mean_datetimelike(self):
         tm.assert_series_equal(result, expected)
 
     @pytest.mark.xfail(
-        reason="casts to object-dtype and then tries to " "add timestamps",
+        reason="casts to object-dtype and then tries to add timestamps",
         raises=TypeError,
         strict=True,
     )
@@ -1643,7 +1641,7 @@ def test_idxmin(self, float_frame, int_frame):
                     expected = df.apply(Series.idxmin, axis=axis, skipna=skipna)
                     tm.assert_series_equal(result, expected)
 
-        msg = "No axis named 2 for object type" " <class 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             frame.idxmin(axis=2)
 
@@ -1658,7 +1656,7 @@ def test_idxmax(self, float_frame, int_frame):
                     expected = df.apply(Series.idxmax, axis=axis, skipna=skipna)
                     tm.assert_series_equal(result, expected)
 
-        msg = "No axis named 2 for object type" " <class 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             frame.idxmax(axis=2)
 

pandas/tests/frame/test_api.py

@@ -149,7 +149,7 @@ def test_not_hashable(self):
         empty_frame = DataFrame()
 
         df = self.klass([1])
-        msg = "'(Sparse)?DataFrame' objects are mutable, thus they cannot be" " hashed"
+        msg = "'(Sparse)?DataFrame' objects are mutable, thus they cannot be hashed"
         with pytest.raises(TypeError, match=msg):
             hash(df)
         with pytest.raises(TypeError, match=msg):

pandas/tests/frame/test_block_internals.py

@@ -286,7 +286,7 @@ def f(dtype):
             data = list(itertools.repeat((datetime(2001, 1, 1), "aa", 20), 9))
             return DataFrame(data=data, columns=["A", "B", "C"], dtype=dtype)
 
-        msg = "compound dtypes are not implemented in the DataFrame" " constructor"
+        msg = "compound dtypes are not implemented in the DataFrame constructor"
         with pytest.raises(NotImplementedError, match=msg):
             f([("A", "datetime64[h]"), ("B", "str"), ("C", "int32")])
 

pandas/tests/frame/test_constructors.py

@@ -474,7 +474,7 @@ def test_constructor_error_msgs(self):
         with pytest.raises(ValueError, match=msg):
             DataFrame((range(10), range(10, 20)), columns=("ones", "twos"))
 
-        msg = "If using all scalar " "values, you must pass " "an index"
+        msg = "If using all scalar values, you must pass an index"
         with pytest.raises(ValueError, match=msg):
             DataFrame({"a": False, "b": True})
 

pandas/tests/frame/test_dtypes.py

@@ -686,9 +686,7 @@ def test_astype_dict_like(self, dtype_class):
         # in the keys of the dtype dict
         dt4 = dtype_class({"b": str, 2: str})
         dt5 = dtype_class({"e": str})
-        msg = (
-            "Only a column name can be used for the key in a dtype mappings" " argument"
-        )
+        msg = "Only a column name can be used for the key in a dtype mappings argument"
         with pytest.raises(KeyError, match=msg):
             df.astype(dt4)
         with pytest.raises(KeyError, match=msg):
@@ -1194,11 +1192,11 @@ def test_astype_str(self, timezone_frame):
         with option_context("display.max_columns", 20):
             result = str(timezone_frame)
             assert (
-                "0 2013-01-01 2013-01-01 00:00:00-05:00 " "2013-01-01 00:00:00+01:00"
+                "0 2013-01-01 2013-01-01 00:00:00-05:00 2013-01-01 00:00:00+01:00"
             ) in result
             assert (
-                "1 2013-01-02                       " "NaT                       NaT"
+                "1 2013-01-02                       NaT                       NaT"
             ) in result
             assert (
-                "2 2013-01-03 2013-01-03 00:00:00-05:00 " "2013-01-03 00:00:00+01:00"
+                "2 2013-01-03 2013-01-03 00:00:00-05:00 2013-01-03 00:00:00+01:00"
             ) in result

pandas/tests/frame/test_missing.py

@@ -126,7 +126,7 @@ def test_dropna(self):
         assert_frame_equal(dropped, expected)
 
         # bad input
-        msg = "No axis named 3 for object type" " <class 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 3 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             df.dropna(axis=3)
 
@@ -362,7 +362,7 @@ def test_na_actions_categorical(self):
         res = df.fillna(value={"cats": 3, "vals": "b"})
         tm.assert_frame_equal(res, df_exp_fill)
 
-        with pytest.raises(ValueError, match=("fill value must " "be in categories")):
+        with pytest.raises(ValueError, match=("fill value must be in categories")):
             df.fillna(value={"cats": 4, "vals": "c"})
 
         res = df.fillna(method="pad")

pandas/tests/frame/test_quantile.py

@@ -90,9 +90,7 @@ def test_quantile_axis_parameter(self):
         result = df.quantile(0.5, axis="columns")
         assert_series_equal(result, expected)
 
-        msg = (
-            "No axis named -1 for object type" " <class 'pandas.core.frame.DataFrame'>"
-        )
+        msg = "No axis named -1 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             df.quantile(0.1, axis=-1)
         msg = (

pandas/tests/frame/test_sorting.py

@@ -55,7 +55,7 @@ def test_sort_values(self):
         sorted_df = frame.sort_values(by=["B", "A"], ascending=[True, False])
         assert_frame_equal(sorted_df, expected)
 
-        msg = "No axis named 2 for object type" " <class 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             frame.sort_values(by=["A", "B"], axis=2, inplace=True)
 

pandas/tests/frame/test_timeseries.py

@@ -901,7 +901,7 @@ def test_frame_to_period(self):
         pts = df.to_period("M", axis=1)
         tm.assert_index_equal(pts.columns, exp.columns.asfreq("M"))
 
-        msg = "No axis named 2 for object type" " <class 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             df.to_period(axis=2)
 

pandas/tests/generic/test_generic.py

@@ -724,10 +724,10 @@ def test_squeeze(self):
         tm.assert_series_equal(df.squeeze(axis=1), df.iloc[:, 0])
         tm.assert_series_equal(df.squeeze(axis="columns"), df.iloc[:, 0])
         assert df.squeeze() == df.iloc[0, 0]
-        msg = "No axis named 2 for object type <class" " 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named 2 for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             df.squeeze(axis=2)
-        msg = "No axis named x for object type <class" " 'pandas.core.frame.DataFrame'>"
+        msg = "No axis named x for object type <class 'pandas.core.frame.DataFrame'>"
         with pytest.raises(ValueError, match=msg):
             df.squeeze(axis="x")
 

pandas/tests/groupby/test_function.py

@@ -92,7 +92,7 @@ def test_builtins_apply(keys, f):
     result = df.groupby(keys).apply(f)
     ngroups = len(df.drop_duplicates(subset=keys))
 
-    assert_msg = "invalid frame shape: {} " "(expected ({}, 3))".format(
+    assert_msg = "invalid frame shape: {} (expected ({}, 3))".format(
         result.shape, ngroups
     )
     assert result.shape == (ngroups, 3), assert_msg
@@ -1220,7 +1220,7 @@ def test_size_groupby_all_null():
 def test_quantile(interpolation, a_vals, b_vals, q):
     if interpolation == "nearest" and q == 0.5 and b_vals == [4, 3, 2, 1]:
         pytest.skip(
-            "Unclear numpy expectation for nearest result with " "equidistant data"
+            "Unclear numpy expectation for nearest result with equidistant data"
         )
 
     a_expected = pd.Series(a_vals).quantile(q, interpolation=interpolation)
@@ -1243,9 +1243,7 @@ def test_quantile_raises():
         [["foo", "a"], ["foo", "b"], ["foo", "c"]], columns=["key", "val"]
     )
 
-    with pytest.raises(
-        TypeError, match="cannot be performed against " "'object' dtypes"
-    ):
+    with pytest.raises(TypeError, match="cannot be performed against 'object' dtypes"):
         df.groupby("key").quantile()
 
 

pandas/tests/groupby/test_grouping.py

@@ -378,7 +378,7 @@ def test_groupby_grouper_f_sanity_checked(self):
             ts.groupby(lambda key: key[0:6])
 
     def test_grouping_error_on_multidim_input(self, df):
-        msg = "Grouper for '<class 'pandas.core.frame.DataFrame'>'" " not 1-dimensional"
+        msg = "Grouper for '<class 'pandas.core.frame.DataFrame'>' not 1-dimensional"
         with pytest.raises(ValueError, match=msg):
             Grouping(df.index, df[["A", "A"]])
 

pandas/tests/groupby/test_transform.py

@@ -768,7 +768,7 @@ def test_transform_with_non_scalar_group():
 @pytest.mark.parametrize("agg_func", ["count", "rank", "size"])
 def test_transform_numeric_ret(cols, exp, comp_func, agg_func):
     if agg_func == "size" and isinstance(cols, list):
-        pytest.xfail("'size' transformation not supported with " "NDFrameGroupy")
+        pytest.xfail("'size' transformation not supported with NDFrameGroupy")
 
     # GH 19200
     df = pd.DataFrame(

pandas/tests/groupby/test_whitelist.py

@@ -232,9 +232,7 @@ def test_groupby_blacklist(df_letters):
     blacklist.extend(to_methods)
 
     # e.g., to_csv
-    defined_but_not_allowed = (
-        "(?:^Cannot.+{0!r}.+{1!r}.+try using the " "'apply' method$)"
-    )
+    defined_but_not_allowed = "(?:^Cannot.+{0!r}.+{1!r}.+try using the 'apply' method$)"
 
     # e.g., query, eval
     not_defined = "(?:^{1!r} object has no attribute {0!r}$)"

pandas/tests/indexes/datetimes/test_construction.py

@@ -663,7 +663,7 @@ def test_constructor_dtype(self):
             DatetimeIndex(idx, dtype="datetime64[ns]")
 
         # this is effectively trying to convert tz's
-        msg = "data is already tz-aware US/Eastern, unable to set specified" " tz: CET"
+        msg = "data is already tz-aware US/Eastern, unable to set specified tz: CET"
         with pytest.raises(TypeError, match=msg):
             DatetimeIndex(idx, dtype="datetime64[ns, CET]")
         msg = "cannot supply both a tz and a dtype with a tz"