CLN: Replace bare exceptions with more descriptive ones

pandas/core/common.py

@@ -580,7 +580,7 @@ def take_2d_multi(arr, indexer, out=None, fill_value=np.nan,
                     mask_info = (row_mask, col_mask), (row_needs, col_needs)
                 if row_needs or col_needs:
                     if out is not None and out.dtype != dtype:
-                        raise Exception('Incompatible type for fill_value')
+                        raise TypeError('Incompatible type for fill_value')
                 else:
                     # if not, then depromote, set fill_value to dummy
                     # (it won't be used but we don't want the cython code
@@ -814,7 +814,7 @@ def changeit():
                 # if we are trying to do something unsafe
                 # like put a bigger dtype in a smaller one, use the smaller one
                 if change.dtype.itemsize < r.dtype.itemsize:
-                    raise Exception("cannot change dtype of input to smaller size")
+                    raise TypeError("cannot change dtype of input to smaller size")
                 change.dtype = r.dtype
                 change[:] = r
 
@@ -1259,7 +1259,7 @@ def ensure_float(arr):
 
 def _mut_exclusive(arg1, arg2):
     if arg1 is not None and arg2 is not None:
-        raise Exception('mutually exclusive arguments')
+        raise TypeError('mutually exclusive arguments')
     elif arg1 is not None:
         return arg1
     else:

pandas/core/format.py

@@ -825,7 +825,7 @@ def __init__(self, obj, path_or_buf, sep=",", na_rep='', float_format=None,
         # validate mi options
         if self.has_mi_columns:
             if cols is not None:
-                raise Exception("cannot specify cols with a multi_index on the columns")
+                raise TypeError("cannot specify cols with a multi_index on the columns")
 
         if cols is not None:
             if isinstance(cols,Index):

pandas/core/frame.py

@@ -933,7 +933,7 @@ def dot(self, other):
             lvals = self.values
             rvals = np.asarray(other)
             if lvals.shape[1] != rvals.shape[0]:
-                raise Exception('Dot product shape mismatch, %s vs %s' %
+                raise ValueError('Dot product shape mismatch, %s vs %s' %
                                 (lvals.shape, rvals.shape))
 
         if isinstance(other, DataFrame):
@@ -2844,7 +2844,7 @@ def set_index(self, keys, drop=True, append=False, inplace=False,
 
         if verify_integrity and not index.is_unique:
             duplicates = index.get_duplicates()
-            raise Exception('Index has duplicate keys: %s' % duplicates)
+            raise ValueError('Index has duplicate keys: %s' % duplicates)
 
         for c in to_remove:
             del frame[c]
@@ -3315,7 +3315,7 @@ def sortlevel(self, level=0, axis=0, ascending=True, inplace=False):
         axis = self._get_axis_number(axis)
         the_axis = self._get_axis(axis)
         if not isinstance(the_axis, MultiIndex):
-            raise Exception('can only sort by level with a hierarchical index')
+            raise TypeError('can only sort by level with a hierarchical index')
 
         new_axis, indexer = the_axis.sortlevel(level, ascending=ascending)
 
@@ -3377,7 +3377,7 @@ def reorder_levels(self, order, axis=0):
         axis = self._get_axis_number(axis)
         if not isinstance(self._get_axis(axis),
                           MultiIndex):  # pragma: no cover
-            raise Exception('Can only reorder levels on a hierarchical axis.')
+            raise TypeError('Can only reorder levels on a hierarchical axis.')
 
         result = self.copy()
 
@@ -3789,7 +3789,7 @@ def rename(self, index=None, columns=None, copy=True, inplace=False):
         from pandas.core.series import _get_rename_function
 
         if index is None and columns is None:
-            raise Exception('must pass either index or columns')
+            raise TypeError('must pass either index or columns')
 
         index_f = _get_rename_function(index)
         columns_f = _get_rename_function(columns)

pandas/core/index.py

@@ -361,7 +361,7 @@ def __hash__(self):
         return hash(self.view(np.ndarray))
 
     def __setitem__(self, key, value):
-        raise Exception(str(self.__class__) + ' object is immutable')
+        raise TypeError(str(self.__class__) + ' does not support item assignment')
 
     def __getitem__(self, key):
         """Override numpy.ndarray's __getitem__ method to work as desired"""
@@ -547,7 +547,7 @@ def order(self, return_indexer=False, ascending=True):
             return sorted_index
 
     def sort(self, *args, **kwargs):
-        raise Exception('Cannot sort an Index object')
+        raise TypeError('Cannot sort an %r object' % self.__class__.__name__)
 
     def shift(self, periods=1, freq=None):
         """
@@ -606,7 +606,7 @@ def union(self, other):
         union : Index
         """
         if not hasattr(other, '__iter__'):
-            raise Exception('Input must be iterable!')
+            raise TypeError('Input must be iterable!')
 
         if len(other) == 0 or self.equals(other):
             return self
@@ -671,7 +671,7 @@ def intersection(self, other):
         intersection : Index
         """
         if not hasattr(other, '__iter__'):
-            raise Exception('Input must be iterable!')
+            raise TypeError('Input must be iterable!')
 
         self._assert_can_do_setop(other)
 
@@ -713,7 +713,7 @@ def diff(self, other):
         """
 
         if not hasattr(other, '__iter__'):
-            raise Exception('Input must be iterable!')
+            raise TypeError('Input must be iterable!')
 
         if self.equals(other):
             return Index([], name=self.name)
@@ -1080,7 +1080,7 @@ def _join_level(self, other, level, how='left', return_indexers=False):
         the MultiIndex will not be changed (currently)
         """
         if isinstance(self, MultiIndex) and isinstance(other, MultiIndex):
-            raise Exception('Join on level between two MultiIndex objects '
+            raise TypeError('Join on level between two MultiIndex objects '
                             'is ambiguous')
 
         left, right = self, other
@@ -2298,7 +2298,7 @@ def _partial_tup_index(self, tup, side='left'):
 
             if lab not in lev:
                 if not lev.is_type_compatible(lib.infer_dtype([lab])):
-                    raise Exception('Level type mismatch: %s' % lab)
+                    raise TypeError('Level type mismatch: %s' % lab)
 
                 # short circuit
                 loc = lev.searchsorted(lab, side=side)
@@ -2738,7 +2738,7 @@ def _ensure_index(index_like):
 
 def _validate_join_method(method):
     if method not in ['left', 'right', 'inner', 'outer']:
-        raise Exception('do not recognize join method %s' % method)
+        raise ValueError('do not recognize join method %s' % method)
 
 
 # TODO: handle index names!

pandas/core/internals.py

@@ -1571,7 +1571,7 @@ def xs(self, key, axis=1, copy=True):
         new_blocks = []
         if len(self.blocks) > 1:
             if not copy:
-                raise Exception('cannot get view of mixed-type or '
+                raise TypeError('cannot get view of mixed-type or '
                                 'non-consolidated DataFrame')
             for blk in self.blocks:
                 newb = make_block(blk.values[slicer], 
@@ -1604,7 +1604,7 @@ def fast_2d_xs(self, loc, copy=False):
             return result
 
         if not copy:
-            raise Exception('cannot get view of mixed-type or '
+            raise TypeError('cannot get view of mixed-type or '
                             'non-consolidated DataFrame')
 
         dtype = _interleaved_dtype(self.blocks)
@@ -2093,7 +2093,7 @@ def _maybe_rename_join(self, other, lsuffix, rsuffix, copydata=True):
         to_rename = self.items.intersection(other.items)
         if len(to_rename) > 0:
             if not lsuffix and not rsuffix:
-                raise Exception('columns overlap: %s' % to_rename)
+                raise ValueError('columns overlap: %s' % to_rename)
 
             def lrenamer(x):
                 if x in to_rename:
@@ -2377,7 +2377,7 @@ def _shape_compat(x):
     else:
         items = _ensure_index([ n for n in names if n in ref_items ])
         if len(items) != len(stacked):
-            raise Exception("invalid names passed _stack_arrays")
+            raise ValueError("invalid names passed _stack_arrays")
 
     return items, stacked, placement
 

pandas/core/panel.py

@@ -137,7 +137,7 @@ def f(self, other):
         if isinstance(other, self._constructor):
             return self._compare_constructor(other, func)
         elif isinstance(other, (self._constructor_sliced, DataFrame, Series)):
-            raise Exception("input needs alignment for this object [%s]" %
+            raise ValueError("input needs alignment for this object [%s]" %
                             self._constructor)
         else:
             return self._combine_const(other, na_op)

pandas/core/panelnd.py

@@ -58,7 +58,7 @@ def create_nd_panel_factory(klass_name, axis_orders, axis_slices, slicer, axis_a
     #### define the methods ####
     def __init__(self, *args, **kwargs):
         if not (kwargs.get('data') or len(args)):
-            raise Exception(
+            raise TypeError(
                 "must supply at least a data argument to [%s]" % klass_name)
         if 'copy' not in kwargs:
             kwargs['copy'] = False

pandas/core/series.py

@@ -1962,7 +1962,8 @@ def clip(self, lower=None, upper=None, out=None):
         clipped : Series
         """
         if out is not None:  # pragma: no cover
-            raise Exception('out argument is not supported yet')
+            # TODO: Support out argument?
+            raise NotImplementedError('out argument is not supported yet')
 
         result = self
         if lower is not None:
@@ -2028,7 +2029,7 @@ def dot(self, other):
             lvals = self.values
             rvals = np.asarray(other)
             if lvals.shape[0] != rvals.shape[0]:
-                raise Exception('Dot product shape mismatch, %s vs %s' %
+                raise ValueError('Dot product shape mismatch, %s vs %s' %
                                 (lvals.shape, rvals.shape))
 
         if isinstance(other, DataFrame):
@@ -2379,7 +2380,7 @@ def sortlevel(self, level=0, ascending=True):
         sorted : Series
         """
         if not isinstance(self.index, MultiIndex):
-            raise Exception('can only sort by level with a hierarchical index')
+            raise TypeError('can only sort by level with a hierarchical index')
 
         new_index, indexer = self.index.sortlevel(level, ascending=ascending)
         new_values = self.values.take(indexer)
@@ -2417,7 +2418,7 @@ def reorder_levels(self, order):
         type of caller (new object)
         """
         if not isinstance(self.index, MultiIndex):  # pragma: no cover
-            raise Exception('Can only reorder levels on a hierarchical axis.')
+            raise TypeError('Can only reorder levels on a hierarchical axis.')
 
         result = self.copy()
         result.index = result.index.reorder_levels(order)
@@ -3156,7 +3157,7 @@ def interpolate(self, method='linear'):
         """
         if method == 'time':
             if not isinstance(self, TimeSeries):
-                raise Exception('time-weighted interpolation only works'
+                raise TypeError('time-weighted interpolation only works'
                                 'on TimeSeries')
             method = 'values'
             # inds = pa.array([d.toordinal() for d in self.index])
@@ -3279,7 +3280,7 @@ def tz_localize(self, tz, copy=True):
 
         if not isinstance(self.index, DatetimeIndex):
             if len(self.index) > 0:
-                raise Exception('Cannot tz-localize non-time series')
+                raise TypeError('Cannot tz-localize non-time series')
 
             new_index = DatetimeIndex([], tz=tz)
         else:
@@ -3413,7 +3414,7 @@ def _try_cast(arr, take_fast_path):
 
     elif subarr.ndim > 1:
         if isinstance(data, pa.Array):
-            raise Exception('Data must be 1-dimensional')
+            raise ValueError('Data must be 1-dimensional')
         else:
             subarr = _asarray_tuplesafe(data, dtype=dtype)
 

pandas/io/excel.py

@@ -368,7 +368,7 @@ def write_cells(self, cells, sheet_name=None, startrow=0, startcol=0):
         if sheet_name is None:
             sheet_name = self.cur_sheet
         if sheet_name is None:  # pragma: no cover
-            raise Exception('Must pass explicit sheet_name or set '
+            raise TypeError('Must pass explicit sheet_name or set '
                             'cur_sheet property')
         if self.use_xlsx:
             self._writecells_xlsx(cells, sheet_name, startrow, startcol)

pandas/rpy/common.py

@@ -195,7 +195,7 @@ def convert_robj(obj, use_pandas=True):
         if isinstance(obj, rpy_type):
             return converter(obj)
 
-    raise Exception('Do not know what to do with %s object' % type(obj))
+    raise TypeError('Do not know what to do with %s object' % type(obj))
 
 
 def convert_to_r_posixct(obj):

pandas/sparse/array.py

@@ -261,7 +261,7 @@ def _get_val_at(self, loc):
             loc += n
 
         if loc >= len(self) or loc < 0:
-            raise Exception('Out of bounds access')
+            raise IndexError('Out of bounds access')
 
         sp_loc = self.sp_index.lookup(loc)
         if sp_loc == -1:
@@ -283,7 +283,7 @@ def take(self, indices, axis=0):
 
         n = len(self)
         if (indices < 0).any() or (indices >= n).any():
-            raise Exception('out of bounds access')
+            raise IndexError('out of bounds access')
 
         if self.sp_index.npoints > 0:
             locs = np.array([self.sp_index.lookup(loc) for loc in indices])
@@ -296,10 +296,10 @@ def take(self, indices, axis=0):
         return result
 
     def __setitem__(self, key, value):
-        raise Exception('SparseArray objects are immutable')
+        raise TypeError('%r object does not support item assignment' % self.__class__.__name__)
 
     def __setslice__(self, i, j, value):
-        raise Exception('SparseArray objects are immutable')
+        raise TypeError('%r object does not support item assignment' % self.__class__.__name__)
 
     def to_dense(self):
         """
@@ -313,7 +313,7 @@ def astype(self, dtype=None):
         """
         dtype = np.dtype(dtype)
         if dtype is not None and dtype not in (np.float_, float):
-            raise Exception('Can only support floating point data for now')
+            raise TypeError('Can only support floating point data for now')
         return self.copy()
 
     def copy(self, deep=True):

pandas/sparse/frame.py

@@ -195,10 +195,10 @@ def _init_matrix(self, data, index, columns, dtype=None):
             columns = _default_index(K)
 
         if len(columns) != K:
-            raise Exception('Column length mismatch: %d vs. %d' %
+            raise ValueError('Column length mismatch: %d vs. %d' %
                             (len(columns), K))
         if len(index) != N:
-            raise Exception('Index length mismatch: %d vs. %d' %
+            raise ValueError('Index length mismatch: %d vs. %d' %
                             (len(index), N))
 
         data = dict([(idx, data[:, i]) for i, idx in enumerate(columns)])
@@ -585,7 +585,7 @@ def _combine_const(self, other, func):
     def _reindex_index(self, index, method, copy, level, fill_value=np.nan,
                        limit=None):
         if level is not None:
-            raise Exception('Reindex by level not supported for sparse')
+            raise TypeError('Reindex by level not supported for sparse')
 
         if self.index.equals(index):
             if copy:
@@ -616,7 +616,7 @@ def _reindex_index(self, index, method, copy, level, fill_value=np.nan,
 
     def _reindex_columns(self, columns, copy, level, fill_value, limit=None):
         if level is not None:
-            raise Exception('Reindex by level not supported for sparse')
+            raise TypeError('Reindex by level not supported for sparse')
 
         if com.notnull(fill_value):
             raise NotImplementedError
@@ -891,7 +891,7 @@ def stack_sparse_frame(frame):
     vals_to_concat = []
     for _, series in frame.iteritems():
         if not np.isnan(series.fill_value):
-            raise Exception('This routine assumes NaN fill value')
+            raise TypeError('This routine assumes NaN fill value')
 
         int_index = series.sp_index.to_int_index()
         inds_to_concat.append(int_index.indices)
@@ -931,7 +931,7 @@ def homogenize(series_dict):
 
     for _, series in series_dict.iteritems():
         if not np.isnan(series.fill_value):
-            raise Exception('this method is only valid with NaN fill values')
+            raise TypeError('this method is only valid with NaN fill values')
 
         if index is None:
             index = series.sp_index