diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py index ffd03096e2a27..cccb094eaae7b 100644 --- a/pandas/core/algorithms.py +++ b/pandas/core/algorithms.py @@ -393,12 +393,12 @@ def isin(comps, values): if not is_list_like(comps): raise TypeError("only list-like objects are allowed to be passed" - " to isin(), you passed a " - "[{0}]".format(type(comps).__name__)) + " to isin(), you passed a [{comps_type}]" + .format(comps_type=type(comps).__name__)) if not is_list_like(values): raise TypeError("only list-like objects are allowed to be passed" - " to isin(), you passed a " - "[{0}]".format(type(values).__name__)) + " to isin(), you passed a [{values_type}]" + .format(values_type=type(values).__name__)) if not isinstance(values, (ABCIndex, ABCSeries, np.ndarray)): values = lib.list_to_object_array(list(values)) @@ -671,7 +671,7 @@ def mode(values): try: result = np.sort(result) except TypeError as e: - warn("Unable to sort modes: %s" % e) + warn("Unable to sort modes: {error}".format(error=e)) result = _reconstruct_data(result, original.dtype, original) return Series(result) diff --git a/pandas/core/base.py b/pandas/core/base.py index 4ae4736035793..a7c991dc8d257 100644 --- a/pandas/core/base.py +++ b/pandas/core/base.py @@ -342,24 +342,25 @@ def _obj_with_exclusions(self): def __getitem__(self, key): if self._selection is not None: - raise Exception('Column(s) %s already selected' % self._selection) + raise Exception('Column(s) {selection} already selected' + .format(selection=self._selection)) if isinstance(key, (list, tuple, ABCSeries, ABCIndexClass, np.ndarray)): if len(self.obj.columns.intersection(key)) != len(key): bad_keys = list(set(key).difference(self.obj.columns)) - raise KeyError("Columns not found: %s" - % str(bad_keys)[1:-1]) + raise KeyError("Columns not found: {missing}" + .format(missing=str(bad_keys)[1:-1])) return self._gotitem(list(key), ndim=2) elif not getattr(self, 'as_index', False): if key not in self.obj.columns: - raise KeyError("Column not found: %s" % key) + raise KeyError("Column not found: {key}".format(key=key)) return self._gotitem(key, ndim=2) else: if key not in self.obj: - raise KeyError("Column not found: %s" % key) + raise KeyError("Column not found: {key}".format(key=key)) return self._gotitem(key, ndim=1) def _gotitem(self, key, ndim, subset=None): @@ -409,7 +410,7 @@ def _try_aggregate_string_function(self, arg, *args, **kwargs): if f is not None: return f(self, *args, **kwargs) - raise ValueError("{} is an unknown string function".format(arg)) + raise ValueError("{arg} is an unknown string function".format(arg=arg)) def _aggregate(self, arg, *args, **kwargs): """ @@ -484,9 +485,9 @@ def nested_renaming_depr(level=4): is_nested_renamer = True if k not in obj.columns: - raise SpecificationError('cannot perform renaming ' - 'for {0} with a nested ' - 'dictionary'.format(k)) + msg = ('cannot perform renaming for {key} with a ' + 'nested dictionary').format(key=k) + raise SpecificationError(msg) nested_renaming_depr(4 + (_level or 0)) elif isinstance(obj, ABCSeries): diff --git a/pandas/core/tools/datetimes.py b/pandas/core/tools/datetimes.py index 6ff4302937d07..53f58660cabdb 100644 --- a/pandas/core/tools/datetimes.py +++ b/pandas/core/tools/datetimes.py @@ -46,7 +46,8 @@ def _infer(a, b): if b and b.tzinfo: if not (tslib.get_timezone(tz) == tslib.get_timezone(b.tzinfo)): raise AssertionError('Inputs must both have the same timezone,' - ' {0} != {1}'.format(tz, b.tzinfo)) + ' {timezone1} != {timezone2}' + .format(timezone1=tz, timezone2=b.tzinfo)) return tz tz = None @@ -491,10 +492,10 @@ def _convert_listlike(arg, box, format, name=None, tz=tz): offset = tslib.Timestamp(origin) - tslib.Timestamp(0) except tslib.OutOfBoundsDatetime: raise tslib.OutOfBoundsDatetime( - "origin {} is Out of Bounds".format(origin)) + "origin {origin} is Out of Bounds".format(origin=origin)) except ValueError: - raise ValueError("origin {} cannot be converted " - "to a Timestamp".format(origin)) + raise ValueError("origin {origin} cannot be converted " + "to a Timestamp".format(origin=origin)) # convert the offset to the unit of the arg # this should be lossless in terms of precision @@ -590,16 +591,16 @@ def f(value): required = ['year', 'month', 'day'] req = sorted(list(set(required) - set(unit_rev.keys()))) if len(req): - raise ValueError("to assemble mappings requires at " - "least that [year, month, day] be specified: " - "[{0}] is missing".format(','.join(req))) + raise ValueError("to assemble mappings requires at least that " + "[year, month, day] be specified: [{required}] " + "is missing".format(required=','.join(req))) # keys we don't recognize excess = sorted(list(set(unit_rev.keys()) - set(_unit_map.values()))) if len(excess): raise ValueError("extra keys have been passed " "to the datetime assemblage: " - "[{0}]".format(','.join(excess))) + "[{excess}]".format(','.join(excess=excess))) def coerce(values): # we allow coercion to if errors allows @@ -617,7 +618,7 @@ def coerce(values): values = to_datetime(values, format='%Y%m%d', errors=errors) except (TypeError, ValueError) as e: raise ValueError("cannot assemble the " - "datetimes: {0}".format(e)) + "datetimes: {error}".format(error=e)) for u in ['h', 'm', 's', 'ms', 'us', 'ns']: value = unit_rev.get(u) @@ -627,8 +628,8 @@ def coerce(values): unit=u, errors=errors) except (TypeError, ValueError) as e: - raise ValueError("cannot assemble the datetimes " - "[{0}]: {1}".format(value, e)) + raise ValueError("cannot assemble the datetimes [{value}]: " + "{error}".format(value=value, error=e)) return values @@ -810,8 +811,10 @@ def _convert_listlike(arg, format): times.append(datetime.strptime(element, format).time()) except (ValueError, TypeError): if errors == 'raise': - raise ValueError("Cannot convert %s to a time with " - "given format %s" % (element, format)) + msg = ("Cannot convert {element} to a time with given " + "format {format}").format(element=element, + format=format) + raise ValueError(msg) elif errors == 'ignore': return arg else: @@ -876,6 +879,7 @@ def ole2datetime(oledt): # Excel has a bug where it thinks the date 2/29/1900 exists # we just reject any date before 3/1/1900. if val < 61: - raise ValueError("Value is outside of acceptable range: %s " % val) + msg = "Value is outside of acceptable range: {value}".format(value=val) + raise ValueError(msg) return OLE_TIME_ZERO + timedelta(days=val) diff --git a/pandas/core/tools/timedeltas.py b/pandas/core/tools/timedeltas.py index f2d99d26a87b8..d5132826bb93f 100644 --- a/pandas/core/tools/timedeltas.py +++ b/pandas/core/tools/timedeltas.py @@ -129,7 +129,8 @@ def _validate_timedelta_unit(arg): except: if arg is None: return 'ns' - raise ValueError("invalid timedelta unit {0} provided".format(arg)) + raise ValueError("invalid timedelta unit {arg} provided" + .format(arg=arg)) def _coerce_scalar_to_timedelta_type(r, unit='ns', box=True, errors='raise'): @@ -161,8 +162,8 @@ def _convert_listlike(arg, unit='ns', box=True, errors='raise', name=None): if is_timedelta64_dtype(arg): value = arg.astype('timedelta64[ns]') elif is_integer_dtype(arg): - value = arg.astype('timedelta64[{0}]'.format( - unit)).astype('timedelta64[ns]', copy=False) + value = arg.astype('timedelta64[{unit}]'.format(unit=unit)).astype( + 'timedelta64[ns]', copy=False) else: try: value = tslib.array_to_timedelta64(_ensure_object(arg),