diff --git a/pandas/core/base.py b/pandas/core/base.py
index cc676b9682277..6c0a0c26b6457 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -19,7 +19,7 @@ class StringMixin(object):
     # Formatting
 
     def __unicode__(self):
-        raise NotImplementedError
+        raise NotImplementedError("StringMixin __unicode__ format")
 
     def __str__(self):
         """
@@ -382,7 +382,7 @@ def _box_func(self):
         """
         box function to get object from internal representation
         """
-        raise NotImplementedError
+        raise NotImplementedError("Box function to get object from internal representation")
 
     def _box_values(self, values):
         """
diff --git a/pandas/core/common.py b/pandas/core/common.py
index 92d60ae8d8847..bad9a03942277 100644
--- a/pandas/core/common.py
+++ b/pandas/core/common.py
@@ -39,6 +39,11 @@ class SettingWithCopyWarning(Warning):
 class AmbiguousIndexError(PandasError, KeyError):
     pass
 
+class AbstractMethodError(NotImplementedError):
+    def __init__(self,m):
+        self.message = m
+    def __str__(self):
+        return "This method must be defined on the concrete class - "+self.message
 
 _POSSIBLY_CAST_DTYPES = set([np.dtype(t).name
                              for t in ['O', 'int8',
@@ -134,7 +139,7 @@ def _isnull_new(obj):
         return lib.checknull(obj)
     # hack (for now) because MI registers as ndarray
     elif isinstance(obj, pd.MultiIndex):
-        raise NotImplementedError("isnull is not defined for MultiIndex")
+        raise AbstractMethodError("isnull is not defined for MultiIndex")
     elif isinstance(obj, (ABCSeries, np.ndarray)):
         return _isnull_ndarraylike(obj)
     elif isinstance(obj, ABCGeneric):
@@ -160,7 +165,7 @@ def _isnull_old(obj):
         return lib.checknull_old(obj)
     # hack (for now) because MI registers as ndarray
     elif isinstance(obj, pd.MultiIndex):
-        raise NotImplementedError("isnull is not defined for MultiIndex")
+        raise AbstractMethodError("isnull is not defined for MultiIndex")
     elif isinstance(obj, (ABCSeries, np.ndarray)):
         return _isnull_ndarraylike_old(obj)
     elif isinstance(obj, ABCGeneric):
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 756de479a471a..3d4a90ed82592 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -135,7 +135,7 @@ def _init_mgr(self, mgr, axes=None, dtype=None, copy=False):
 
     @property
     def _constructor(self):
-        raise NotImplementedError
+        raise NotImplementedError("NDFrame _constructor")
 
     def __unicode__(self):
         # unicode representation based upon iterating over self
@@ -150,7 +150,7 @@ def _local_dir(self):
 
     @property
     def _constructor_sliced(self):
-        raise NotImplementedError
+        raise NotImplementedError("NDFrame _constructor_sliced")
 
     #----------------------------------------------------------------------
     # Axis
@@ -1073,7 +1073,7 @@ def _iget_item_cache(self, item):
         return lower
 
     def _box_item_values(self, key, values):
-        raise NotImplementedError
+        raise NotImplementedError("NDFrame _box_item_values")
 
     def _maybe_cache_changed(self, item, value):
         """
@@ -1653,7 +1653,7 @@ def _needs_reindex_multi(self, axes, method, level):
                 method is None and level is None and not self._is_mixed_type)
 
     def _reindex_multi(self, axes, copy, fill_value):
-        return NotImplemented
+        raise NotImplementedError("NDFrame _reindex_multi")
 
     _shared_docs['reindex_axis'] = (
         """Conform input object to new index with optional filling logic,
@@ -2179,7 +2179,7 @@ def fillna(self, value=None, method=None, axis=0, inplace=False,
                 raise ValueError('must specify a fill method or value')
             if self._is_mixed_type and axis == 1:
                 if inplace:
-                    raise NotImplementedError()
+                    raise NotImplementedError("fillna with inplace=True and _is_mixed_type=True and axis=1")
                 result = self.T.fillna(method=method, limit=limit).T
 
                 # need to downcast here because of all of the transposes
@@ -2880,7 +2880,7 @@ def first(self, offset):
         """
         from pandas.tseries.frequencies import to_offset
         if not isinstance(self.index, DatetimeIndex):
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for DatatimeIndex instance only")
 
         if len(self.index) == 0:
             return self
@@ -2914,7 +2914,7 @@ def last(self, offset):
         """
         from pandas.tseries.frequencies import to_offset
         if not isinstance(self.index, DatetimeIndex):
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for DatatimeIndex instance only")
 
         if len(self.index) == 0:
             return self
diff --git a/pandas/core/groupby.py b/pandas/core/groupby.py
index c2debb9bfe1c0..abba9f352da44 100644
--- a/pandas/core/groupby.py
+++ b/pandas/core/groupby.py
@@ -283,7 +283,7 @@ def _set_grouper(self, obj, sort=False):
         return self.grouper
 
     def _get_binner_for_grouping(self, obj):
-        raise NotImplementedError
+        raise NotImplementedError("Binner for grouping")
 
     @property
     def groups(self):
@@ -644,7 +644,7 @@ def _python_apply_general(self, f):
                                          not_indexed_same=mutated)
 
     def aggregate(self, func, *args, **kwargs):
-        raise NotImplementedError
+        raise NotImplementedError("Groupby aggregrate")
 
     @Appender(_agg_doc)
     def agg(self, func, *args, **kwargs):
@@ -654,7 +654,7 @@ def _iterate_slices(self):
         yield self.name, self._selected_obj
 
     def transform(self, func, *args, **kwargs):
-        raise NotImplementedError
+        raise NotImplementedError("Groupby transform")
 
     def mean(self):
         """
@@ -1041,7 +1041,7 @@ def _python_agg_general(self, func, *args, **kwargs):
         return self._wrap_aggregated_output(output)
 
     def _wrap_applied_output(self, *args, **kwargs):
-        raise NotImplementedError
+        raise NotImplementedError("Groupby wrap applied output")
 
     def _concat_objects(self, keys, values, not_indexed_same=False):
         from pandas.tools.merge import concat
@@ -1404,7 +1404,7 @@ def aggregate(self, values, how, axis=0):
                 swapped = True
                 values = values.swapaxes(0, axis)
             if arity > 1:
-                raise NotImplementedError
+                raise NotImplementedError("BaseGrouper aggregate for arity > 1")
             out_shape = (self.ngroups,) + values.shape[1:]
 
         if is_numeric_dtype(values.dtype):
@@ -1459,7 +1459,7 @@ def _aggregate(self, result, counts, values, how, is_numeric):
         comp_ids, _, ngroups = self.group_info
         if values.ndim > 3:
             # punting for now
-            raise NotImplementedError
+            raise NotImplementedError("BaseGrouper aggregrate for > 3 dimensions")
         elif values.ndim > 2:
             for i, chunk in enumerate(values.transpose(2, 0, 1)):
 
@@ -1695,7 +1695,7 @@ def _aggregate(self, result, counts, values, how, is_numeric=True):
 
         if values.ndim > 3:
             # punting for now
-            raise NotImplementedError
+            raise NotImplementedError("BinGrouper aggregate for > 3 dimensions")
         elif values.ndim > 2:
             for i, chunk in enumerate(values.transpose(2, 0, 1)):
                 agg_func(result[:, :, i], counts, chunk, self.bins)
@@ -2399,7 +2399,7 @@ def aggregate(self, arg, *args, **kwargs):
             if self._selection is not None:
                 subset = obj
                 if isinstance(subset, DataFrame):
-                    raise NotImplementedError
+                    raise NotImplementedError("aggregate not implemented for subset being a Dataframe")
 
                 for fname, agg_how in compat.iteritems(arg):
                     colg = SeriesGroupBy(subset, selection=self._selection,
@@ -2459,7 +2459,7 @@ def _aggregate_multiple_funcs(self, arg):
         from pandas.tools.merge import concat
 
         if self.axis != 0:
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for axis = 0")
 
         obj = self._obj_with_exclusions
 
@@ -2509,7 +2509,7 @@ def _aggregate_generic(self, func, *args, **kwargs):
         return self._wrap_generic_output(result, obj)
 
     def _wrap_aggregated_output(self, output, names=None):
-        raise NotImplementedError
+        raise NotImplementedError("NDFrameGroupBy wrap aggregated output")
 
     def _aggregate_item_by_item(self, func, *args, **kwargs):
         # only for axis==0
@@ -3050,7 +3050,7 @@ def _iterate_slices(self):
                 slice_axis = self._selection_list
             slicer = lambda x: self._selected_obj[x]
         else:
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for axis = 0")
 
         for val in slice_axis:
             if val in self.exclusions:
@@ -3115,10 +3115,10 @@ def _aggregate_item_by_item(self, func, *args, **kwargs):
             new_axes[self.axis] = self.grouper.result_index
             return Panel._from_axes(result, new_axes)
         else:
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for axis>0")
 
     def _wrap_aggregated_output(self, output, names=None):
-        raise NotImplementedError
+        raise NotImplementedError("PanelGroupBy _wrap_aggregated_output")
 
 
 class NDArrayGroupBy(GroupBy):
@@ -3172,7 +3172,7 @@ def _chop(self, sdata, slice_obj):
         return sdata.iloc[slice_obj]
 
     def apply(self, f):
-        raise NotImplementedError
+        raise NotImplementedError("DataSplitter apply function")
 
 
 class ArraySplitter(DataSplitter):
diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 280c4073b0f94..860422c058d77 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -7,7 +7,7 @@
 import pandas.core.common as com
 from pandas.core.common import (_is_bool_indexer, is_integer_dtype,
                                 _asarray_tuplesafe, is_list_like, isnull,
-                                ABCSeries, ABCDataFrame, ABCPanel, is_float)
+                                ABCSeries, ABCDataFrame, ABCPanel, is_float, AbstractMethodError)
 import pandas.lib as lib
 
 import numpy as np
@@ -55,7 +55,7 @@ def __call__(self, *args, **kwargs):
         return self
 
     def __iter__(self):
-        raise NotImplementedError('ix is not iterable')
+        raise AbstractMethodError('ix is not iterable')
 
     def __getitem__(self, key):
         if type(key) is tuple:
@@ -120,7 +120,7 @@ def __setitem__(self, key, value):
         self._setitem_with_indexer(indexer, value)
 
     def _has_valid_type(self, k, axis):
-        raise NotImplementedError()
+        raise AbstractMethodError("Valid type checking for _NDFrameIndexer is not implemented")
 
     def _has_valid_tuple(self, key):
         """ check the key for valid keys across my indexer """
@@ -644,7 +644,7 @@ def _align_frame(self, indexer, df):
     def _align_panel(self, indexer, df):
         is_frame = self.obj.ndim == 2
         is_panel = self.obj.ndim >= 3
-        raise NotImplementedError("cannot set using an indexer with a Panel "
+        raise AbstractMethodError("cannot set using an indexer with a Panel "
                                   "yet!")
 
     def _getitem_tuple(self, tup):
@@ -1141,7 +1141,7 @@ def __getitem__(self, key):
             return self._getitem_axis(key, axis=0)
 
     def _getitem_axis(self, key, axis=0, validate_iterable=False):
-        raise NotImplementedError()
+        raise AbstractMethodError("Get item along given axis in _LocationIndexer is not implemented")
 
     def _getbool_axis(self, key, axis=0):
         labels = self.obj._get_axis(axis)
@@ -1299,7 +1299,7 @@ def _has_valid_type(self, key, axis):
         if com._is_bool_indexer(key):
             if hasattr(key, 'index') and isinstance(key.index, Index):
                 if key.index.inferred_type == 'integer':
-                    raise NotImplementedError(
+                    raise AbstractMethodError(
                         "iLocation based boolean indexing on an integer type "
                         "is not available"
                     )
diff --git a/pandas/core/internals.py b/pandas/core/internals.py
index 8100b98d6e42d..884dab11e8808 100644
--- a/pandas/core/internals.py
+++ b/pandas/core/internals.py
@@ -243,7 +243,7 @@ def fillna(self, value, limit=None, inplace=False, downcast=None):
         mask = isnull(self.values)
         if limit is not None:
             if self.ndim > 2:
-                raise NotImplementedError
+                raise NotImplementedError("fillna function not implemented for more than 2 dimensions")
             mask[mask.cumsum(self.ndim-1)>limit]=False
 
         value = self._try_fill(value)
@@ -363,10 +363,10 @@ def convert(self, copy=True, **kwargs):
         return [self.copy()] if copy else [self]
 
     def _can_hold_element(self, value):
-        raise NotImplementedError()
+        raise NotImplementedError("Block _can_hold_element function")
 
     def _try_cast(self, value):
-        raise NotImplementedError()
+        raise NotImplementedError("Block _try_cast")
 
     def _try_cast_result(self, result, dtype=None):
         """ try to cast the result to our original type,
@@ -1519,7 +1519,7 @@ def fillna(self, value, limit=None,
         value = self._try_fill(value)
         if limit is not None:
             if self.ndim > 2:
-                raise NotImplementedError
+                raise NotImplementedError("fillna function not implemented for more than 2 dimensions")
             mask[mask.cumsum(self.ndim-1)>limit]=False
 
         np.putmask(values, mask, value)
@@ -1741,7 +1741,7 @@ def interpolate(self, method='pad', axis=0, inplace=False,
     def fillna(self, value, limit=None, inplace=False, downcast=None):
         # we may need to upcast our fill to match our dtype
         if limit is not None:
-            raise NotImplementedError
+            raise NotImplementedError("fillna currently implemented only for limit=None")
         if issubclass(self.dtype.type, np.floating):
             value = float(value)
         values = self.values if inplace else self.values.copy()
diff --git a/pandas/core/panel.py b/pandas/core/panel.py
index e9f8893355f2d..1cd867a5233ba 100644
--- a/pandas/core/panel.py
+++ b/pandas/core/panel.py
@@ -595,10 +595,10 @@ def conform(self, frame, axis='items'):
         return frame.reindex(**self._extract_axes_for_slice(self, axes))
 
     def head(self, n=5):
-        raise NotImplementedError
+        raise NotImplementedError("Returns the head content of a Panel")
 
     def tail(self, n=5):
-        raise NotImplementedError
+        raise NotImplementedError("Returns the tail content of a Panel")
 
     def _needs_reindex_multi(self, axes, method, level):
         """ don't allow a multi reindex on Panel or above ndim """
diff --git a/pandas/core/panelnd.py b/pandas/core/panelnd.py
index 3eebd51190e3d..73ba07f845e87 100644
--- a/pandas/core/panelnd.py
+++ b/pandas/core/panelnd.py
@@ -99,7 +99,7 @@ def _combine_with_constructor(self, other, func):
     for f in ['to_frame', 'to_excel', 'to_sparse', 'groupby', 'join', 'filter',
               'dropna', 'shift']:
         def func(self, *args, **kwargs):
-            raise NotImplementedError
+            raise NotImplementedError("%s is not implemented" % f)
         setattr(klass, f, func)
 
     # add the aggregate operations
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 78b049f4bf8d5..2ed3f9c854817 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -156,7 +156,7 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                 dtype = self._validate_dtype(dtype)
 
             if isinstance(data, MultiIndex):
-                raise NotImplementedError
+                raise NotImplementedError("Series initialization currently is not implemented for MultiIndex")
             elif isinstance(data, Index):
                 # need to copy to avoid aliasing issues
                 if name is None:
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index ad64d2bf6bdd9..0591131f986b6 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -680,7 +680,7 @@ def str_slice_replace(arr, start=None, stop=None, repl=None):
     -------
     replaced : array
     """
-    raise NotImplementedError
+    raise NotImplementedError("String slice replace not implemented")
 
 
 def str_strip(arr, to_strip=None):
@@ -985,7 +985,7 @@ def slice(self, start=None, stop=None, step=1):
 
     @copy(str_slice)
     def slice_replace(self, i=None, j=None):
-        raise NotImplementedError
+        raise NotImplementedError("String slice replace is not implemented.")
 
     @copy(str_decode)
     def decode(self, encoding, errors="strict"):
diff --git a/pandas/index.pyx b/pandas/index.pyx
index 3dcdbf207fb3f..ab1bea2abb22c 100644
--- a/pandas/index.pyx
+++ b/pandas/index.pyx
@@ -234,10 +234,10 @@ cdef class IndexEngine:
         self._ensure_mapping_populated()
 
     def _call_monotonic(self, values):
-        raise NotImplementedError
+        raise NotImplementedError("IndexEngine _call_monotonic is not implemented")
 
     cdef _make_hash_table(self, n):
-        raise NotImplementedError
+        raise NotImplementedError("IndexEngine _make_hash_table is not implemented")
 
     cdef _check_type(self, object val):
         hash(val)
diff --git a/pandas/io/ga.py b/pandas/io/ga.py
index f002994888932..9ee6a64c1affc 100644
--- a/pandas/io/ga.py
+++ b/pandas/io/ga.py
@@ -240,7 +240,7 @@ def get_profile(self, account_id=None, web_property_id=None, name=None,
         return _get_match(profiles, name, id, **kwargs)
 
     def create_query(self, *args, **kwargs):
-        raise NotImplementedError()
+        raise NotImplementedError("Create query in GDataReader is not implemented")
 
     @Substitution(extras='')
     @Appender(_GA_READER_DOC)
diff --git a/pandas/io/html.py b/pandas/io/html.py
index 5ea6ca36ac764..39da36f84a3aa 100644
--- a/pandas/io/html.py
+++ b/pandas/io/html.py
@@ -215,7 +215,7 @@ def _text_getter(self, obj):
         text : str or unicode
             The text from an individual DOM node.
         """
-        raise NotImplementedError
+        raise NotImplementedError("Text from an individual DOM node")
 
     def _parse_td(self, obj):
         """Return the td elements from a row element.
@@ -229,7 +229,7 @@ def _parse_td(self, obj):
         columns : list of node-like
             These are the elements of each row, i.e., the columns.
         """
-        raise NotImplementedError
+        raise NotImplementedError("Elements of each row, i.e the columns")
 
     def _parse_tables(self, doc, match, attrs):
         """Return all tables from the parsed DOM.
@@ -256,7 +256,7 @@ def _parse_tables(self, doc, match, attrs):
         tables : list of node-like
             A list of <table> elements to be parsed into raw data.
         """
-        raise NotImplementedError
+        raise NotImplementedError("All tables from the parsed DOM")
 
     def _parse_tr(self, table):
         """Return the list of row elements from the parsed table element.
@@ -271,7 +271,7 @@ def _parse_tr(self, table):
         rows : list of node-like
             A list row elements of a table, usually <tr> or <th> elements.
         """
-        raise NotImplementedError
+        raise NotImplementedError("List of row elements from parsed table element")
 
     def _parse_thead(self, table):
         """Return the header of a table.
@@ -286,7 +286,7 @@ def _parse_thead(self, table):
         thead : node-like
             A <thead>...</thead> element.
         """
-        raise NotImplementedError
+        raise NotImplementedError("Header of HTML table")
 
     def _parse_tbody(self, table):
         """Return the body of the table.
@@ -301,7 +301,7 @@ def _parse_tbody(self, table):
         tbody : node-like
             A <tbody>...</tbody> element.
         """
-        raise NotImplementedError
+        raise NotImplementedError("Body of HTML table")
 
     def _parse_tfoot(self, table):
         """Return the footer of the table if any.
@@ -316,7 +316,7 @@ def _parse_tfoot(self, table):
         tfoot : node-like
             A <tfoot>...</tfoot> element.
         """
-        raise NotImplementedError
+        raise NotImplementedError("Footer of HTML table")
 
     def _build_doc(self):
         """Return a tree-like object that can be used to iterate over the DOM.
@@ -325,7 +325,7 @@ def _build_doc(self):
         -------
         obj : tree-like
         """
-        raise NotImplementedError
+        raise NotImplementedError("Tree-like object to iterate over the DOM")
 
     def _build_table(self, table):
         header = self._parse_raw_thead(table)
diff --git a/pandas/io/json.py b/pandas/io/json.py
index 4ed325df9a747..a0d350bf9dfc1 100644
--- a/pandas/io/json.py
+++ b/pandas/io/json.py
@@ -33,7 +33,7 @@ def to_json(path_or_buf, obj, orient=None, date_format='epoch',
             double_precision=double_precision, ensure_ascii=force_ascii,
             date_unit=date_unit, default_handler=default_handler).write()
     else:
-        raise NotImplementedError
+        raise NotImplementedError("to_json is currently implemented for Series and Dataframe only.")
 
     if isinstance(path_or_buf, compat.string_types):
         with open(path_or_buf, 'w') as fh:
@@ -64,7 +64,7 @@ def __init__(self, obj, orient, date_format, double_precision,
         self._format_axes()
 
     def _format_axes(self):
-        raise NotImplementedError
+        raise NotImplementedError("Writer _format_axes is not implemented")
 
     def write(self):
         return dumps(
@@ -282,7 +282,7 @@ def _convert_axes(self):
                 setattr(self.obj, axis, new_axis)
 
     def _try_convert_types(self):
-        raise NotImplementedError
+        raise NotImplementedError("Try to convert types in Parser is not implemented.")
 
     def _try_convert_data(self, name, data, use_dtypes=True,
                           convert_dates=True):
@@ -395,7 +395,7 @@ def _try_convert_to_date(self, data):
         return data, False
 
     def _try_convert_dates(self):
-        raise NotImplementedError
+        raise NotImplementedError("Try to convert dates in Parser is not implemented")
 
 
 class SeriesParser(Parser):
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index 22fe3ef16e34d..9f4fcd863727e 100644
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -679,7 +679,7 @@ def _make_engine(self, engine='c'):
             self._engine = klass(self.f, **self.options)
 
     def _failover_to_python(self):
-        raise NotImplementedError
+        raise NotImplementedError("Failover to Python not implemented")
 
     def read(self, nrows=None):
         if nrows is not None:
diff --git a/pandas/io/sql.py b/pandas/io/sql.py
index bb6f9cee5766e..c22c5b448dd57 100644
--- a/pandas/io/sql.py
+++ b/pandas/io/sql.py
@@ -427,7 +427,7 @@ def to_sql(frame, name, con, flavor='sqlite', if_exists='fail', index=True,
     if isinstance(frame, Series):
         frame = frame.to_frame()
     elif not isinstance(frame, DataFrame):
-        raise NotImplementedError
+        raise NotImplementedError("Currently to_sql() implemented only for Series and DataFrame")
 
     pandas_sql.to_sql(frame, name, if_exists=if_exists, index=index,
                       index_label=index_label)
@@ -983,7 +983,7 @@ def __init__(self, con, flavor, is_cursor=False):
         if flavor is None:
             flavor = 'sqlite'
         if flavor not in ['sqlite', 'mysql']:
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for sqlite and mysql flavors only")
         else:
             self.flavor = flavor
 
diff --git a/pandas/io/tests/test_parsers.py b/pandas/io/tests/test_parsers.py
index c02a3172f4adc..feeb1cbee296d 100644
--- a/pandas/io/tests/test_parsers.py
+++ b/pandas/io/tests/test_parsers.py
@@ -52,10 +52,10 @@ class ParserTests(object):
 """
 
     def read_csv(self, *args, **kwargs):
-        raise NotImplementedError
+        raise NotImplementedError("Read CSV in Parser Tests is not implemented")
 
     def read_table(self, *args, **kwargs):
-        raise NotImplementedError
+        raise NotImplementedError("Read Table in Parser Tests is not implemented")
 
     def setUp(self):
         import warnings
diff --git a/pandas/io/tests/test_sql.py b/pandas/io/tests/test_sql.py
index a34f278fc5a96..da88d0fc1203b 100644
--- a/pandas/io/tests/test_sql.py
+++ b/pandas/io/tests/test_sql.py
@@ -727,10 +727,10 @@ def setup_import(self):
             raise nose.SkipTest('SQLAlchemy not installed')
 
     def setup_driver(self):
-        raise NotImplementedError()
+        raise NotImplementedError("SQLAlchemy Setup Driver test not implemented")
 
     def connect(self):
-        raise NotImplementedError()
+        raise NotImplementedError("SQLAlchemy Connect test not implemented")
 
     def setup_connect(self):
         try:
@@ -740,7 +740,7 @@ def setup_connect(self):
             raise nose.SkipTest("Can't connect to {0} server".format(self.flavor))
 
     def tearDown(self):
-        raise NotImplementedError()
+        raise NotImplementedError("SQLAlchemy Tear Down test not implemented")
 
     def test_aread_sql(self):
         self._read_sql_iris()
diff --git a/pandas/sparse/frame.py b/pandas/sparse/frame.py
index bd34c7e5f02b2..46c952c58ae21 100644
--- a/pandas/sparse/frame.py
+++ b/pandas/sparse/frame.py
@@ -250,7 +250,7 @@ def to_dense(self):
         return DataFrame(data, index=self.index)
 
     def astype(self, dtype):
-        raise NotImplementedError
+        raise NotImplementedError("SparseDataFrame astype not implemented")
 
     def copy(self, deep=True):
         """
@@ -419,7 +419,7 @@ def _combine_frame(self, other, func, fill_value=None, level=None):
         new_index, new_columns = this.index, this.columns
 
         if level is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Combine Frames implemented only for level=None.")
 
         if self.empty and other.empty:
             return SparseDataFrame(index=new_index).__finalize__(self)
@@ -460,9 +460,9 @@ def _combine_match_index(self, other, func, level=None, fill_value=None):
         new_data = {}
 
         if fill_value is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Combine match index implemented for fill_value=None only")
         if level is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Combine match index implemented for level=None only")
 
         new_index = self.index.union(other.index)
         this = self
@@ -495,9 +495,10 @@ def _combine_match_columns(self, other, func, level=None, fill_value=None):
         # possible for this to happen, which is bothersome
 
         if fill_value is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Combine match columns implemented for fill_value=None only")
         if level is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Combine match columns implemented for level=None only")
+
 
         new_data = {}
 
@@ -568,10 +569,10 @@ def _reindex_columns(self, columns, copy, level, fill_value, limit=None,
             raise TypeError('Reindex by level not supported for sparse')
 
         if com.notnull(fill_value):
-            raise NotImplementedError
+            raise NotImplementedError("Currently reindexing for com.nonnull(fillvalue)=True is not implemented")
 
         if limit:
-            raise NotImplementedError
+            raise NotImplementedError("Currently limit=None is only implemented")
 
         # TODO: fill value handling
         sdict = dict((k, v) for k, v in compat.iteritems(self) if k in columns)
diff --git a/pandas/sparse/list.py b/pandas/sparse/list.py
index bfc4ab9d3eb48..c75fbf2ee10fb 100644
--- a/pandas/sparse/list.py
+++ b/pandas/sparse/list.py
@@ -46,7 +46,7 @@ def __getitem__(self, i):
         return self._chunks[j][i - passed]
 
     def __setitem__(self, i, value):
-        raise NotImplementedError
+        raise NotImplementedError("set item in SparseList is not implemented")
 
     @property
     def nchunks(self):
diff --git a/pandas/sparse/panel.py b/pandas/sparse/panel.py
index 20bbc58cc908f..b1b6889e8823c 100644
--- a/pandas/sparse/panel.py
+++ b/pandas/sparse/panel.py
@@ -32,7 +32,7 @@ def __set__(self, obj, value):
         value = _ensure_index(value)
 
         if isinstance(value, MultiIndex):
-            raise NotImplementedError
+            raise NotImplementedError("Currently Sparse Panel Axis does not support MutliIndex")
 
         for v in compat.itervalues(obj._frames):
             setattr(v, self.frame_attr, value)
@@ -155,7 +155,7 @@ def _get_items(self):
     def _set_items(self, new_items):
         new_items = _ensure_index(new_items)
         if isinstance(new_items, MultiIndex):
-            raise NotImplementedError
+            raise NotImplementedError("Currently Sparse Panel Axis does not support MutliIndex")
 
         # need to create new frames dict
 
diff --git a/pandas/src/generate_code.py b/pandas/src/generate_code.py
index b432ddd03d17f..d17b689fb1640 100644
--- a/pandas/src/generate_code.py
+++ b/pandas/src/generate_code.py
@@ -1619,7 +1619,7 @@ def group_ohlc_%(name)s(ndarray[%(dest_type2)s, ndim=2] out,
 
     b = 0
     if K > 1:
-        raise NotImplementedError
+        raise NotImplementedError("group aggregation for K>1 is not implemented")
     else:
         for i in range(N):
             while b < ngroups - 1 and i >= bins[b]:
diff --git a/pandas/src/generated.pyx b/pandas/src/generated.pyx
index 42ae043847ba1..6f2feb5c7679d 100644
--- a/pandas/src/generated.pyx
+++ b/pandas/src/generated.pyx
@@ -6505,7 +6505,7 @@ def group_ohlc_float64(ndarray[float64_t, ndim=2] out,
 
     b = 0
     if K > 1:
-        raise NotImplementedError
+        raise NotImplementedError("group aggregation for K>1 is not implemented")
     else:
         for i in range(N):
             while b < ngroups - 1 and i >= bins[b]:
@@ -6578,7 +6578,7 @@ def group_ohlc_float32(ndarray[float32_t, ndim=2] out,
 
     b = 0
     if K > 1:
-        raise NotImplementedError
+        raise NotImplementedError("group aggregation for K>1 is not implemented")
     else:
         for i in range(N):
             while b < ngroups - 1 and i >= bins[b]:
diff --git a/pandas/src/sparse.pyx b/pandas/src/sparse.pyx
index 579d473cae1b3..6a9855176d20b 100644
--- a/pandas/src/sparse.pyx
+++ b/pandas/src/sparse.pyx
@@ -27,7 +27,7 @@ cdef class SparseIndex:
     Abstract superclass for sparse index types
     '''
     def __init__(self):
-        raise NotImplementedError
+        raise NotImplementedError("Initialization of Supercall SparseIndex is not implemented")
 
 
 cdef class IntIndex(SparseIndex):
@@ -556,7 +556,7 @@ cdef class BlockMerge(object):
         self.result = self._make_merged_blocks()
 
     cdef _make_merged_blocks(self):
-        raise NotImplementedError
+        raise NotImplementedError("BlockMerge _make_merged_blocks not implemented")
 
     cdef _set_current_indices(self, int32_t xi, int32_t yi, bint mode):
         if mode == 0:
diff --git a/pandas/tools/plotting.py b/pandas/tools/plotting.py
index 37a982acc0bbd..5b29fc8a7b7fc 100644
--- a/pandas/tools/plotting.py
+++ b/pandas/tools/plotting.py
@@ -127,7 +127,7 @@ def random_color(column):
 
             colors = lmap(random_color, lrange(num_colors))
         else:
-            raise NotImplementedError
+            raise NotImplementedError("color_type = default/random are only implemented")
 
     if len(colors) != num_colors:
         multiple = num_colors//len(colors) - 1
@@ -989,7 +989,7 @@ def _compute_plot_data(self):
         self.data = numeric_data
 
     def _make_plot(self):
-        raise NotImplementedError
+        raise NotImplementedError("MPLPlot _make_plot not implemented")
 
     def _add_table(self):
         if self.table is False:
@@ -1828,7 +1828,7 @@ def f(ax, x, y, w, start=None, log=self.log, **kwds):
                     start = start + self.left
                 return ax.barh(x, y, w, left=start, **kwds)
         else:
-            raise NotImplementedError
+            raise NotImplementedError("Plot with kind = 'bar'/'barh' are only implemented")
 
         return f
 
diff --git a/pandas/tseries/index.py b/pandas/tseries/index.py
index ff585d80af830..7ed2541af06f7 100644
--- a/pandas/tseries/index.py
+++ b/pandas/tseries/index.py
@@ -1717,14 +1717,14 @@ def indexer_at_time(self, time, asof=False):
         from dateutil.parser import parse
 
         if asof:
-            raise NotImplementedError
+            raise NotImplementedError("Currently selection of values is implemented for asof=False")
 
         if isinstance(time, compat.string_types):
             time = parse(time).time()
 
         if time.tzinfo:
             # TODO
-            raise NotImplementedError
+            raise NotImplementedError("Currently datetime.time or string is supported")
 
         time_micros = self._get_time_micros()
         micros = _time_to_micros(time)
@@ -1756,7 +1756,7 @@ def indexer_between_time(self, start_time, end_time, include_start=True,
             end_time = parse(end_time).time()
 
         if start_time.tzinfo or end_time.tzinfo:
-            raise NotImplementedError
+            raise NotImplementedError("Currently implemented for datetime.time and string")
 
         time_micros = self._get_time_micros()
         start_micros = _time_to_micros(start_time)
@@ -1858,7 +1858,7 @@ def _generate_regular_range(start, end, periods, offset):
             b = e - periods * stride
             tz = end.tz
         else:
-            raise NotImplementedError
+            raise NotImplementedError("start and end are None, periods is not None is not currently implemented")
 
         data = np.arange(b, e, stride, dtype=np.int64)
         data = DatetimeIndex._simple_new(data, None, tz=tz)
diff --git a/pandas/tseries/resample.py b/pandas/tseries/resample.py
index 059a6bfd06719..7e52683bca739 100644
--- a/pandas/tseries/resample.py
+++ b/pandas/tseries/resample.py
@@ -346,11 +346,11 @@ def _take_new_index(obj, indexer, new_index, axis=0):
         return Series(new_values, index=new_index, name=obj.name)
     elif isinstance(obj, DataFrame):
         if axis == 1:
-            raise NotImplementedError
+            raise NotImplementedError("Taking new index of a Dataframe not implemented for axis=1")
         return DataFrame(obj._data.reindex_indexer(
             new_axis=new_index, indexer=indexer, axis=1))
     else:
-        raise NotImplementedError
+        raise NotImplementedError("Taking new index implemented only for Series and DataFrame")
 
 
 def _get_range_edges(axis, offset, closed='left', base=0):
@@ -429,7 +429,7 @@ def asfreq(obj, freq, method=None, how=None, normalize=False):
     """
     if isinstance(obj.index, PeriodIndex):
         if method is not None:
-            raise NotImplementedError
+            raise NotImplementedError("Currently utility frequency conversion implemented for method=None")
 
         if how is None:
             how = 'E'