STY: Spaces over concat strings - batch 1

pandas/_libs/tslib.pyx

@@ -120,8 +120,7 @@ def ints_to_pydatetime(const int64_t[:] arr, object tz=None, object freq=None,
     elif box == "datetime":
         func_create = create_datetime_from_ts
     else:
-        raise ValueError("box must be one of 'datetime', 'date', 'time' or"
-                         " 'timestamp'")
+        raise ValueError("box must be one of 'datetime', 'date', 'time' or 'timestamp'")
 
     if is_utc(tz) or tz is None:
         for i in range(n):

pandas/_libs/tslibs/strptime.pyx

@@ -278,8 +278,8 @@ def array_strptime(object[:] values, object fmt,
                                  "the ISO year directive '%G' and a weekday "
                                  "directive '%A', '%a', '%w', or '%u'.")
             else:
-                raise ValueError("ISO week directive '%V' is incompatible with"
-                                 " the year directive '%Y'. Use the ISO year "
+                raise ValueError("ISO week directive '%V' is incompatible with "
+                                 "the year directive '%Y'. Use the ISO year "
                                  "'%G' instead.")
 
         # If we know the wk of the year and what day of that wk, we can figure

pandas/_libs/tslibs/timestamps.pyx

@@ -814,9 +814,9 @@ default 'raise'
                                'shift_backward')
         if nonexistent not in nonexistent_options and not isinstance(
             nonexistent, timedelta):
-            raise ValueError("The nonexistent argument must be one of 'raise',"
-                             " 'NaT', 'shift_forward', 'shift_backward' or"
-                             " a timedelta object")
+            raise ValueError("The nonexistent argument must be one of 'raise', "
+                             "'NaT', 'shift_forward', 'shift_backward' or "
+                             "a timedelta object")
 
         if self.tzinfo is None:
             # tz naive, localize

pandas/core/arrays/datetimes.py

@@ -324,8 +324,7 @@ def __init__(self, values, dtype=_NS_DTYPE, freq=None, copy=False):
         if not isinstance(values, np.ndarray):
             msg = (
                 f"Unexpected type '{type(values).__name__}'. 'values' must be "
-                "a DatetimeArray ndarray, or Series or Index containing one of"
-                " those."
+                "a DatetimeArray ndarray, or Series or Index containing one of those."
             )
             raise ValueError(msg)
         if values.ndim not in [1, 2]:

pandas/core/arrays/timedeltas.py

@@ -230,8 +230,8 @@ def __init__(self, values, dtype=_TD_DTYPE, freq=None, copy=False):
 
         if not isinstance(values, np.ndarray):
             msg = (
-                f"Unexpected type '{type(values).__name__}'. 'values' must be a"
-                " TimedeltaArray ndarray, or Series or Index containing one of those."
+                f"Unexpected type '{type(values).__name__}'. 'values' must be a "
+                "TimedeltaArray ndarray, or Series or Index containing one of those."
             )
             raise ValueError(msg)
         if values.ndim not in [1, 2]:

pandas/core/computation/eval.py

@@ -339,8 +339,8 @@ def eval(
         if parsed_expr.assigner is None:
             if multi_line:
                 raise ValueError(
-                    "Multi-line expressions are only valid"
-                    " if all expressions contain an assignment"
+                    "Multi-line expressions are only valid "
+                    "if all expressions contain an assignment"
                 )
             elif inplace:
                 raise ValueError("Cannot operate inplace if there is no assignment")

pandas/core/frame.py

@@ -7000,8 +7000,8 @@ def append(self, other, ignore_index=False, verify_integrity=False, sort=False):
                 other = Series(other)
             if other.name is None and not ignore_index:
                 raise TypeError(
-                    "Can only append a Series if ignore_index=True"
-                    " or if the Series has a name"
+                    "Can only append a Series if ignore_index=True "
+                    "or if the Series has a name"
                 )
 
             index = Index([other.name], name=self.index.name)

pandas/core/generic.py

@@ -6428,8 +6428,8 @@ def replace(
             if not is_dict_like(to_replace):
                 if not is_dict_like(regex):
                     raise TypeError(
-                        'If "to_replace" and "value" are both None'
-                        ' and "to_replace" is not a list, then '
+                        'If "to_replace" and "value" are both None '
+                        'and "to_replace" is not a list, then '
                         "regex must be a mapping"
                     )
                 to_replace = regex
@@ -6443,9 +6443,8 @@ def replace(
             if any(are_mappings):
                 if not all(are_mappings):
                     raise TypeError(
-                        "If a nested mapping is passed, all values"
-                        " of the top level mapping must be "
-                        "mappings"
+                        "If a nested mapping is passed, all values "
+                        "of the top level mapping must be mappings"
                     )
                 # passed a nested dict/Series
                 to_rep_dict = {}

pandas/core/groupby/groupby.py

@@ -485,8 +485,8 @@ def get_converter(s):
                 except KeyError:
                     # turns out it wasn't a tuple
                     msg = (
-                        "must supply a same-length tuple to get_group"
-                        " with multiple grouping keys"
+                        "must supply a same-length tuple to get_group "
+                        "with multiple grouping keys"
                     )
                     raise ValueError(msg)
 

pandas/core/groupby/grouper.py

@@ -605,8 +605,8 @@ def is_in_obj(gpr) -> bool:
 
         if is_categorical_dtype(gpr) and len(gpr) != obj.shape[axis]:
             raise ValueError(
-                f"Length of grouper ({len(gpr)}) and axis ({obj.shape[axis]})"
-                " must be same length"
+                f"Length of grouper ({len(gpr)}) and axis ({obj.shape[axis]}) "
+                "must be same length"
             )
 
         # create the Grouping

pandas/core/indexes/multi.py

@@ -2073,9 +2073,8 @@ def drop(self, codes, level=None, errors="raise"):
                 elif com.is_bool_indexer(loc):
                     if self.lexsort_depth == 0:
                         warnings.warn(
-                            "dropping on a non-lexsorted multi-index"
-                            " without a level parameter may impact "
-                            "performance.",
+                            "dropping on a non-lexsorted multi-index "
+                            "without a level parameter may impact performance.",
                             PerformanceWarning,
                             stacklevel=3,
                         )

pandas/core/resample.py

@@ -1076,10 +1076,9 @@ def _upsample(self, method, limit=None, fill_value=None):
             raise AssertionError("axis must be 0")
         if self._from_selection:
             raise ValueError(
-                "Upsampling from level= or on= selection"
-                " is not supported, use .set_index(...)"
-                " to explicitly set index to"
-                " datetime-like"
+                "Upsampling from level= or on= selection "
+                "is not supported, use .set_index(...) "
+                "to explicitly set index to datetime-like"
             )
 
         ax = self.ax
@@ -1135,9 +1134,9 @@ def _convert_obj(self, obj):
         if self._from_selection:
             # see GH 14008, GH 12871
             msg = (
-                "Resampling from level= or on= selection"
-                " with a PeriodIndex is not currently supported,"
-                " use .set_index(...) to explicitly set index"
+                "Resampling from level= or on= selection "
+                "with a PeriodIndex is not currently supported, "
+                "use .set_index(...) to explicitly set index"
             )
             raise NotImplementedError(msg)
 

pandas/core/reshape/concat.py

@@ -351,8 +351,8 @@ def __init__(
         for obj in objs:
             if not isinstance(obj, (Series, DataFrame)):
                 msg = (
-                    "cannot concatenate object of type '{typ}';"
-                    " only Series and DataFrame objs are valid".format(typ=type(obj))
+                    "cannot concatenate object of type '{typ}'; "
+                    "only Series and DataFrame objs are valid".format(typ=type(obj))
                 )
                 raise TypeError(msg)
 
@@ -402,8 +402,8 @@ def __init__(
         self._is_series = isinstance(sample, Series)
         if not 0 <= axis <= sample.ndim:
             raise AssertionError(
-                "axis must be between 0 and {ndim}, input was"
-                " {axis}".format(ndim=sample.ndim, axis=axis)
+                "axis must be between 0 and {ndim}, input was "
+                "{axis}".format(ndim=sample.ndim, axis=axis)
             )
 
         # if we have mixed ndims, then convert to highest ndim
@@ -648,8 +648,8 @@ def _make_concat_multiindex(indexes, keys, levels=None, names=None) -> MultiInde
             # make sure that all of the passed indices have the same nlevels
             if not len({idx.nlevels for idx in indexes}) == 1:
                 raise AssertionError(
-                    "Cannot concat indices that do"
-                    " not have the same number of levels"
+                    "Cannot concat indices that do "
+                    "not have the same number of levels"
                 )
 
             # also copies

pandas/core/reshape/melt.py

@@ -51,8 +51,8 @@ def melt(
             missing = Index(com.flatten(id_vars)).difference(cols)
             if not missing.empty:
                 raise KeyError(
-                    "The following 'id_vars' are not present"
-                    " in the DataFrame: {missing}"
+                    "The following 'id_vars' are not present "
+                    "in the DataFrame: {missing}"
                     "".format(missing=list(missing))
                 )
     else:
@@ -73,8 +73,8 @@ def melt(
             missing = Index(com.flatten(value_vars)).difference(cols)
             if not missing.empty:
                 raise KeyError(
-                    "The following 'value_vars' are not present in"
-                    " the DataFrame: {missing}"
+                    "The following 'value_vars' are not present in "
+                    "the DataFrame: {missing}"
                     "".format(missing=list(missing))
                 )
         frame = frame.loc[:, id_vars + value_vars]

pandas/core/reshape/merge.py

@@ -1246,32 +1246,32 @@ def _validate(self, validate: str):
         if validate in ["one_to_one", "1:1"]:
             if not left_unique and not right_unique:
                 raise MergeError(
-                    "Merge keys are not unique in either left"
-                    " or right dataset; not a one-to-one merge"
+                    "Merge keys are not unique in either left "
+                    "or right dataset; not a one-to-one merge"
                 )
             elif not left_unique:
                 raise MergeError(
-                    "Merge keys are not unique in left dataset;"
-                    " not a one-to-one merge"
+                    "Merge keys are not unique in left dataset; "
+                    "not a one-to-one merge"
                 )
             elif not right_unique:
                 raise MergeError(
-                    "Merge keys are not unique in right dataset;"
-                    " not a one-to-one merge"
+                    "Merge keys are not unique in right dataset; "
+                    "not a one-to-one merge"
                 )
 
         elif validate in ["one_to_many", "1:m"]:
             if not left_unique:
                 raise MergeError(
-                    "Merge keys are not unique in left dataset;"
-                    " not a one-to-many merge"
+                    "Merge keys are not unique in left dataset; "
+                    "not a one-to-many merge"
                 )
 
         elif validate in ["many_to_one", "m:1"]:
             if not right_unique:
                 raise MergeError(
-                    "Merge keys are not unique in right dataset;"
-                    " not a many-to-one merge"
+                    "Merge keys are not unique in right dataset; "
+                    "not a many-to-one merge"
                 )
 
         elif validate in ["many_to_many", "m:m"]:

pandas/core/strings.py

@@ -438,8 +438,8 @@ def str_contains(arr, pat, case=True, flags=0, na=np.nan, regex=True):
 
         if regex.groups > 0:
             warnings.warn(
-                "This pattern has match groups. To actually get the"
-                " groups, use str.extract.",
+                "This pattern has match groups. To actually get the "
+                "groups, use str.extract.",
                 UserWarning,
                 stacklevel=3,
             )

pandas/io/clipboards.py

@@ -69,8 +69,8 @@ def read_clipboard(sep=r"\s+", **kwargs):  # pragma: no cover
         kwargs["engine"] = "python"
     elif len(sep) > 1 and kwargs.get("engine") == "c":
         warnings.warn(
-            "read_clipboard with regex separator does not work"
-            " properly with c engine"
+            "read_clipboard with regex separator does not work "
+            "properly with c engine"
         )
 
     return read_csv(StringIO(text), sep=sep, **kwargs)

pandas/io/excel/_util.py

@@ -154,8 +154,8 @@ def _validate_freeze_panes(freeze_panes):
             return True
 
         raise ValueError(
-            "freeze_panes must be of form (row, column)"
-            " where row and column are integers"
+            "freeze_panes must be of form (row, column) "
+            "where row and column are integers"
         )
 
     # freeze_panes wasn't specified, return False so it won't be applied

pandas/io/formats/format.py

@@ -579,8 +579,8 @@ def __init__(
         else:
             raise ValueError(
                 (
-                    "Formatters length({flen}) should match"
-                    " DataFrame number of columns({dlen})"
+                    "Formatters length({flen}) should match "
+                    "DataFrame number of columns({dlen})"
                 ).format(flen=len(formatters), dlen=len(frame.columns))
             )
         self.na_rep = na_rep

pandas/io/formats/style.py

@@ -1272,9 +1272,9 @@ def bar(
             color = [color[0], color[0]]
         elif len(color) > 2:
             raise ValueError(
-                "`color` must be string or a list-like"
-                " of length 2: [`color_neg`, `color_pos`]"
-                " (eg: color=['#d65f5f', '#5fba7d'])"
+                "`color` must be string or a list-like "
+                "of length 2: [`color_neg`, `color_pos`] "
+                "(eg: color=['#d65f5f', '#5fba7d'])"
             )
 
         subset = _maybe_numeric_slice(self.data, subset)

pandas/io/parsers.py

@@ -612,9 +612,9 @@ def parser_f(
 
         if delim_whitespace and delimiter != default_sep:
             raise ValueError(
-                "Specified a delimiter with both sep and"
-                " delim_whitespace=True; you can only"
-                " specify one."
+                "Specified a delimiter with both sep and "
+                "delim_whitespace=True; you can only "
+                "specify one."
             )
 
         if engine is not None:
@@ -956,8 +956,8 @@ def _clean_options(self, options, engine):
         if sep is None and not delim_whitespace:
             if engine == "c":
                 fallback_reason = (
-                    "the 'c' engine does not support"
-                    " sep=None with delim_whitespace=False"
+                    "the 'c' engine does not support "
+                    "sep=None with delim_whitespace=False"
                 )
                 engine = "python"
         elif sep is not None and len(sep) > 1:
@@ -1120,9 +1120,9 @@ def _make_engine(self, engine="c"):
                 klass = FixedWidthFieldParser
             else:
                 raise ValueError(
-                    f"Unknown engine: {engine} (valid options are"
-                    ' "c", "python", or'
-                    ' "python-fwf")'
+                    f"Unknown engine: {engine} (valid options are "
+                    '"c", "python", or '
+                    '"python-fwf")'
                 )
             self._engine = klass(self.f, **self.options)
 

pandas/io/pytables.py

@@ -1215,9 +1215,8 @@ def append_to_multiple(
         """
         if axes is not None:
             raise TypeError(
-                "axes is currently not accepted as a parameter to"
-                " append_to_multiple; you can create the "
-                "tables independently instead"
+                "axes is currently not accepted as a parameter to append_to_multiple; "
+                "you can create the tables independently instead"
             )
 
         if not isinstance(d, dict):
@@ -3548,9 +3547,8 @@ def create_index(self, columns=None, optlevel=None, kind: Optional[str] = None):
                 if not v.is_indexed:
                     if v.type.startswith("complex"):
                         raise TypeError(
-                            "Columns containing complex values can be stored "
-                            "but cannot"
-                            " be indexed when using table format. Either use "
+                            "Columns containing complex values can be stored but "
+                            "cannot be indexed when using table format. Either use "
                             "fixed format, set index=False, or do not include "
                             "the columns containing complex values to "
                             "data_columns when initializing the table."

pandas/plotting/_matplotlib/core.py

@@ -229,10 +229,9 @@ def _validate_color_args(self):
                 for char in s:
                     if char in matplotlib.colors.BASE_COLORS:
                         raise ValueError(
-                            "Cannot pass 'style' string with a color "
-                            "symbol and 'color' keyword argument. Please"
-                            " use one or the other or pass 'style' "
-                            "without a color symbol"
+                            "Cannot pass 'style' string with a color symbol and "
+                            "'color' keyword argument. Please use one or the other or "
+                            "pass 'style' without a color symbol"
                         )
 
     def _iter_data(self, data=None, keep_index=False, fillna=None):