From f75ca6e5cbe17f99fbad98f1d52ab5d87200fa7b Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 21:31:18 -0700
Subject: [PATCH 1/7] Added test case

---
 pandas/tests/io/test_pytables.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/pandas/tests/io/test_pytables.py b/pandas/tests/io/test_pytables.py
index a6a38e005b9b6..3c2d09663df15 100644
--- a/pandas/tests/io/test_pytables.py
+++ b/pandas/tests/io/test_pytables.py
@@ -1462,6 +1462,17 @@ def test_to_hdf_with_min_itemsize(self):
             tm.assert_series_equal(pd.read_hdf(path, 'ss4'),
                                    pd.concat([df['B'], df2['B']]))
 
+    @pytest.mark.parametrize("format", ['fixed', 'table'])
+    def test_to_hdf_errors(self, format):
+
+        ser = pd.Series(['\ud800foo'])
+        with ensure_clean_path(self.path) as path:
+            # GH 20835
+            ser.to_hdf(path, 'table', format=format, errors='surrogatepass')
+
+            result = pd.read_hdf(path, 'table')
+            tm.assert_series_equal(result, ser)
+
     def test_append_with_data_columns(self):
 
         with ensure_clean_store(self.path) as store:

From 97f6a54a18d9c82f9a9031a632b8cb6dc7e6c18b Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 22:27:40 -0700
Subject: [PATCH 2/7] Round trippable read/write with errors

---
 pandas/io/pytables.py            | 38 ++++++++++++++++++--------------
 pandas/tests/io/test_pytables.py |  2 +-
 2 files changed, 23 insertions(+), 17 deletions(-)

diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 4004a6ea8f6ff..d0dd7a58e4475 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -1566,14 +1566,14 @@ def infer(self, handler):
         new_self.read_metadata(handler)
         return new_self
 
-    def convert(self, values, nan_rep, encoding):
+    def convert(self, values, nan_rep, encoding, errors='strict'):
         """ set the values from this selection: take = take ownership """
 
         # values is a recarray
         if values.dtype.fields is not None:
             values = values[self.cname]
 
-        values = _maybe_convert(values, self.kind, encoding)
+        values = _maybe_convert(values, self.kind, encoding, errors=errors)
 
         kwargs = dict()
         if self.freq is not None:
@@ -1922,7 +1922,8 @@ def set_atom(self, block, block_items, existing_col, min_itemsize,
                 existing_col,
                 min_itemsize,
                 nan_rep,
-                encoding)
+                encoding,
+                **kwargs)
 
         # set as a data block
         else:
@@ -1932,7 +1933,7 @@ def get_atom_string(self, block, itemsize):
         return _tables().StringCol(itemsize=itemsize, shape=block.shape[0])
 
     def set_atom_string(self, block, block_items, existing_col, min_itemsize,
-                        nan_rep, encoding):
+                        nan_rep, encoding, errors='strict'):
         # fill nan items with myself, don't disturb the blocks by
         # trying to downcast
         block = block.fillna(nan_rep, downcast=False)
@@ -1958,7 +1959,7 @@ def set_atom_string(self, block, block_items, existing_col, min_itemsize,
                     )
 
         # itemsize is the maximum length of a string (along any dimension)
-        data_converted = _convert_string_array(data, encoding)
+        data_converted = _convert_string_array(data, encoding, errors=errors)
         itemsize = data_converted.itemsize
 
         # specified min_itemsize?
@@ -2089,7 +2090,7 @@ def validate_attr(self, append):
                 raise ValueError("appended items dtype do not match existing "
                                  "items dtype in table!")
 
-    def convert(self, values, nan_rep, encoding):
+    def convert(self, values, nan_rep, encoding, errors='strict'):
         """set the data from this selection (and convert to the correct dtype
         if we can)
         """
@@ -2163,7 +2164,7 @@ def convert(self, values, nan_rep, encoding):
         # convert nans / decode
         if _ensure_decoded(self.kind) == u('string'):
             self.data = _unconvert_string_array(
-                self.data, nan_rep=nan_rep, encoding=encoding)
+                self.data, nan_rep=nan_rep, encoding=encoding, errors=errors)
 
         return self
 
@@ -3340,9 +3341,11 @@ def read_axes(self, where, **kwargs):
         values = self.selection.select()
 
         # convert the data
+        errors = kwargs.get('errors', 'strict')
         for a in self.axes:
             a.set_info(self.info)
-            a.convert(values, nan_rep=self.nan_rep, encoding=self.encoding)
+            a.convert(values, nan_rep=self.nan_rep, encoding=self.encoding,
+                      errors=errors)
 
         return True
 
@@ -4540,7 +4543,7 @@ def _unconvert_index_legacy(data, kind, legacy=False, encoding=None):
     return index
 
 
-def _convert_string_array(data, encoding, itemsize=None):
+def _convert_string_array(data, encoding, itemsize=None, errors='strict'):
     """
     we take a string-like that is object dtype and coerce to a fixed size
     string type
@@ -4550,6 +4553,7 @@ def _convert_string_array(data, encoding, itemsize=None):
     data : a numpy array of object dtype
     encoding : None or string-encoding
     itemsize : integer, optional, defaults to the max length of the strings
+    errors : handler for encoding errors, default 'strict'
 
     Returns
     -------
@@ -4559,7 +4563,7 @@ def _convert_string_array(data, encoding, itemsize=None):
     # encode if needed
     if encoding is not None and len(data):
         data = Series(data.ravel()).str.encode(
-            encoding).values.reshape(data.shape)
+            encoding, errors).values.reshape(data.shape)
 
     # create the sized dtype
     if itemsize is None:
@@ -4570,7 +4574,7 @@ def _convert_string_array(data, encoding, itemsize=None):
     return data
 
 
-def _unconvert_string_array(data, nan_rep=None, encoding=None):
+def _unconvert_string_array(data, nan_rep=None, encoding=None, errors='strict'):
     """
     inverse of _convert_string_array
 
@@ -4579,6 +4583,7 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None):
     data : fixed length string dtyped array
     nan_rep : the storage repr of NaN, optional
     encoding : the encoding of the data, optional
+    errors : handler for encoding errors, default 'strict'
 
     Returns
     -------
@@ -4600,7 +4605,7 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None):
             dtype = "S{0}".format(itemsize)
 
         if isinstance(data[0], compat.binary_type):
-            data = Series(data).str.decode(encoding).values
+            data = Series(data).str.decode(encoding, errors=errors).values
         else:
             data = data.astype(dtype, copy=False).astype(object, copy=False)
 
@@ -4611,22 +4616,23 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None):
     return data.reshape(shape)
 
 
-def _maybe_convert(values, val_kind, encoding):
+def _maybe_convert(values, val_kind, encoding, errors='strict'):
     if _need_convert(val_kind):
-        conv = _get_converter(val_kind, encoding)
+        conv = _get_converter(val_kind, encoding, errors=errors)
         # conv = np.frompyfunc(conv, 1, 1)
         values = conv(values)
     return values
 
 
-def _get_converter(kind, encoding):
+def _get_converter(kind, encoding, errors='strict'):
     kind = _ensure_decoded(kind)
     if kind == 'datetime64':
         return lambda x: np.asarray(x, dtype='M8[ns]')
     elif kind == 'datetime':
         return lambda x: to_datetime(x, cache=True).to_pydatetime()
     elif kind == 'string':
-        return lambda x: _unconvert_string_array(x, encoding=encoding)
+        return lambda x: _unconvert_string_array(x, encoding=encoding,
+                                                 errors=errors)
     else:  # pragma: no cover
         raise ValueError('invalid kind %s' % kind)
 
diff --git a/pandas/tests/io/test_pytables.py b/pandas/tests/io/test_pytables.py
index 3c2d09663df15..b0efb5b4b6c14 100644
--- a/pandas/tests/io/test_pytables.py
+++ b/pandas/tests/io/test_pytables.py
@@ -1470,7 +1470,7 @@ def test_to_hdf_errors(self, format):
             # GH 20835
             ser.to_hdf(path, 'table', format=format, errors='surrogatepass')
 
-            result = pd.read_hdf(path, 'table')
+            result = pd.read_hdf(path, 'table', errors='surrogatepass')
             tm.assert_series_equal(result, ser)
 
     def test_append_with_data_columns(self):

From 9ae2ea08f948538c8f94e8cac33f36edb9a5e9b1 Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 22:39:06 -0700
Subject: [PATCH 3/7] Added index to test case

---
 pandas/tests/io/test_pytables.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pandas/tests/io/test_pytables.py b/pandas/tests/io/test_pytables.py
index b0efb5b4b6c14..366d1645089f3 100644
--- a/pandas/tests/io/test_pytables.py
+++ b/pandas/tests/io/test_pytables.py
@@ -1465,7 +1465,8 @@ def test_to_hdf_with_min_itemsize(self):
     @pytest.mark.parametrize("format", ['fixed', 'table'])
     def test_to_hdf_errors(self, format):
 
-        ser = pd.Series(['\ud800foo'])
+        data = ['\ud800foo']
+        ser = pd.Series(data, index=pd.Index(data))
         with ensure_clean_path(self.path) as path:
             # GH 20835
             ser.to_hdf(path, 'table', format=format, errors='surrogatepass')

From cfe09d14cb0602572a5cb530df9171ad899f73ad Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 23:09:10 -0700
Subject: [PATCH 4/7] Mirrored encoding impl

---
 pandas/io/pytables.py | 79 +++++++++++++++++++++++++------------------
 1 file changed, 46 insertions(+), 33 deletions(-)

diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index d0dd7a58e4475..9ac954e6ead06 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -705,7 +705,7 @@ def select(self, key, where=None, start=None, stop=None, columns=None,
         def func(_start, _stop, _where):
             return s.read(start=_start, stop=_stop,
                           where=_where,
-                          columns=columns, **kwargs)
+                          columns=columns)
 
         # create the iterator
         it = TableIterator(self, s, func, where=where, nrows=s.nrows,
@@ -1566,14 +1566,14 @@ def infer(self, handler):
         new_self.read_metadata(handler)
         return new_self
 
-    def convert(self, values, nan_rep, encoding, errors='strict'):
+    def convert(self, values, nan_rep, encoding, errors):
         """ set the values from this selection: take = take ownership """
 
         # values is a recarray
         if values.dtype.fields is not None:
             values = values[self.cname]
 
-        values = _maybe_convert(values, self.kind, encoding, errors=errors)
+        values = _maybe_convert(values, self.kind, encoding, errors)
 
         kwargs = dict()
         if self.freq is not None:
@@ -1748,7 +1748,7 @@ class GenericIndexCol(IndexCol):
     def is_indexed(self):
         return False
 
-    def convert(self, values, nan_rep, encoding):
+    def convert(self, values, nan_rep, encoding, errors):
         """ set the values from this selection: take = take ownership """
 
         self.values = Int64Index(np.arange(self.table.nrows))
@@ -1877,7 +1877,7 @@ def set_kind(self):
                 self.typ = getattr(self.description, self.cname, None)
 
     def set_atom(self, block, block_items, existing_col, min_itemsize,
-                 nan_rep, info, encoding=None, **kwargs):
+                 nan_rep, info, encoding=None, errors='strict'):
         """ create and setup my atom from the block b """
 
         self.values = list(block_items)
@@ -1923,7 +1923,7 @@ def set_atom(self, block, block_items, existing_col, min_itemsize,
                 min_itemsize,
                 nan_rep,
                 encoding,
-                **kwargs)
+                errors)
 
         # set as a data block
         else:
@@ -1933,7 +1933,7 @@ def get_atom_string(self, block, itemsize):
         return _tables().StringCol(itemsize=itemsize, shape=block.shape[0])
 
     def set_atom_string(self, block, block_items, existing_col, min_itemsize,
-                        nan_rep, encoding, errors='strict'):
+                        nan_rep, encoding, errors):
         # fill nan items with myself, don't disturb the blocks by
         # trying to downcast
         block = block.fillna(nan_rep, downcast=False)
@@ -1959,7 +1959,7 @@ def set_atom_string(self, block, block_items, existing_col, min_itemsize,
                     )
 
         # itemsize is the maximum length of a string (along any dimension)
-        data_converted = _convert_string_array(data, encoding, errors=errors)
+        data_converted = _convert_string_array(data, encoding, errors)
         itemsize = data_converted.itemsize
 
         # specified min_itemsize?
@@ -2090,7 +2090,7 @@ def validate_attr(self, append):
                 raise ValueError("appended items dtype do not match existing "
                                  "items dtype in table!")
 
-    def convert(self, values, nan_rep, encoding, errors='strict'):
+    def convert(self, values, nan_rep, encoding, errors):
         """set the data from this selection (and convert to the correct dtype
         if we can)
         """
@@ -2230,10 +2230,11 @@ class Fixed(StringMixin):
     ndim = None
     is_table = False
 
-    def __init__(self, parent, group, encoding=None, **kwargs):
+    def __init__(self, parent, group, encoding=None, errors='strict', **kwargs):
         self.parent = parent
         self.group = group
         self.encoding = _ensure_encoding(encoding)
+        self.errors = errors
         self.set_version()
 
     @property
@@ -2437,10 +2438,12 @@ def is_exists(self):
     def set_attrs(self):
         """ set our object attributes """
         self.attrs.encoding = self.encoding
+        self.attrs.errors = self.errors
 
     def get_attrs(self):
         """ retrieve our attributes """
         self.encoding = _ensure_encoding(getattr(self.attrs, 'encoding', None))
+        self.errors = getattr(self.attrs, 'errors', 'strict')
         for n in self.attributes:
             setattr(self, n, _ensure_decoded(getattr(self.attrs, n, None)))
 
@@ -2507,7 +2510,7 @@ def write_index(self, key, index):
             self.write_sparse_intindex(key, index)
         else:
             setattr(self.attrs, '%s_variety' % key, 'regular')
-            converted = _convert_index(index, self.encoding,
+            converted = _convert_index(index, self.encoding, self.errors,
                                        self.format_type).set_name('index')
 
             self.write_array(key, converted.values)
@@ -2553,7 +2556,7 @@ def write_multi_index(self, key, index):
                                                  index.names)):
             # write the level
             level_key = '%s_level%d' % (key, i)
-            conv_level = _convert_index(lev, self.encoding,
+            conv_level = _convert_index(lev, self.encoding, self.errors,
                                         self.format_type).set_name(level_key)
             self.write_array(level_key, conv_level.values)
             node = getattr(self.group, level_key)
@@ -2614,11 +2617,13 @@ def read_index_node(self, node, start=None, stop=None):
 
         if kind in (u('date'), u('datetime')):
             index = factory(_unconvert_index(data, kind,
-                                             encoding=self.encoding),
+                                             encoding=self.encoding,
+                                             errors=self.errors),
                             dtype=object, **kwargs)
         else:
             index = factory(_unconvert_index(data, kind,
-                                             encoding=self.encoding), **kwargs)
+                                             encoding=self.encoding,
+                                             errors=self.errors), **kwargs)
 
         index.name = name
 
@@ -2731,7 +2736,8 @@ def read_index_legacy(self, key, start=None, stop=None):
         node = getattr(self.group, key)
         data = node[start:stop]
         kind = node._v_attrs.kind
-        return _unconvert_index_legacy(data, kind, encoding=self.encoding)
+        return _unconvert_index_legacy(data, kind, encoding=self.encoding,
+                                       errors=self.errors)
 
 
 class LegacySeriesFixed(LegacyFixed):
@@ -3150,7 +3156,8 @@ def write_metadata(self, key, values):
         """
         values = Series(values)
         self.parent.put(self._get_metadata_path(key), values, format='table',
-                        encoding=self.encoding, nan_rep=self.nan_rep)
+                        encoding=self.encoding, errors=self.errors,
+                        nan_rep=self.nan_rep)
 
     def read_metadata(self, key):
         """ return the meta data array for this key """
@@ -3171,6 +3178,7 @@ def set_attrs(self):
         self.attrs.data_columns = self.data_columns
         self.attrs.nan_rep = self.nan_rep
         self.attrs.encoding = self.encoding
+        self.attrs.errors = self.errors
         self.attrs.levels = self.levels
         self.attrs.metadata = self.metadata
         self.set_info()
@@ -3186,6 +3194,7 @@ def get_attrs(self):
         self.nan_rep = getattr(self.attrs, 'nan_rep', None)
         self.encoding = _ensure_encoding(
             getattr(self.attrs, 'encoding', None))
+        self.errors = getattr(self.attrs, 'errors', 'strict')
         self.levels = getattr(
             self.attrs, 'levels', None) or []
         self.index_axes = [
@@ -3341,11 +3350,10 @@ def read_axes(self, where, **kwargs):
         values = self.selection.select()
 
         # convert the data
-        errors = kwargs.get('errors', 'strict')
         for a in self.axes:
             a.set_info(self.info)
             a.convert(values, nan_rep=self.nan_rep, encoding=self.encoding,
-                      errors=errors)
+                      errors=self.errors)
 
         return True
 
@@ -3427,6 +3435,7 @@ def create_axes(self, axes, obj, validate=True, nan_rep=None,
             data_columns = existing_table.data_columns
             nan_rep = existing_table.nan_rep
             self.encoding = existing_table.encoding
+            self.errors = existing_table.errors
             self.info = copy.copy(existing_table.info)
         else:
             existing_table = None
@@ -3453,7 +3462,7 @@ def create_axes(self, axes, obj, validate=True, nan_rep=None,
             if i in axes:
                 name = obj._AXIS_NAMES[i]
                 index_axes_map[i] = _convert_index(
-                    a, self.encoding, self.format_type
+                    a, self.encoding, self.errors, self.format_type
                 ).set_name(name).set_axis(i)
             else:
 
@@ -3572,8 +3581,8 @@ def get_blk_items(mgr, blocks):
                              min_itemsize=min_itemsize,
                              nan_rep=nan_rep,
                              encoding=self.encoding,
-                             info=self.info,
-                             **kwargs)
+                             errors=self.errors,
+                             info=self.info)
                 col.set_pos(j)
 
                 self.values_axes.append(col)
@@ -3737,7 +3746,8 @@ def read_column(self, column, where=None, start=None, stop=None, **kwargs):
                 a.set_info(self.info)
                 return Series(_set_tz(a.convert(c[start:stop],
                                                 nan_rep=self.nan_rep,
-                                                encoding=self.encoding
+                                                encoding=self.encoding,
+                                                errors=self.errors
                                                 ).take_data(),
                                       a.tz, True), name=column)
 
@@ -4418,7 +4428,7 @@ def _set_tz(values, tz, preserve_UTC=False, coerce=False):
     return values
 
 
-def _convert_index(index, encoding=None, format_type=None):
+def _convert_index(index, encoding=None, errors='strict', format_type=None):
     index_name = getattr(index, 'name', None)
 
     if isinstance(index, DatetimeIndex):
@@ -4472,7 +4482,7 @@ def _convert_index(index, encoding=None, format_type=None):
         # atom = _tables().ObjectAtom()
         # return np.asarray(values, dtype='O'), 'object', atom
 
-        converted = _convert_string_array(values, encoding)
+        converted = _convert_string_array(values, encoding, errors)
         itemsize = converted.dtype.itemsize
         return IndexCol(
             converted, 'string', _tables().StringCol(itemsize),
@@ -4503,7 +4513,7 @@ def _convert_index(index, encoding=None, format_type=None):
                         index_name=index_name)
 
 
-def _unconvert_index(data, kind, encoding=None):
+def _unconvert_index(data, kind, encoding=None, errors='strict'):
     kind = _ensure_decoded(kind)
     if kind == u('datetime64'):
         index = DatetimeIndex(data)
@@ -4522,7 +4532,8 @@ def _unconvert_index(data, kind, encoding=None):
     elif kind in (u('integer'), u('float')):
         index = np.asarray(data)
     elif kind in (u('string')):
-        index = _unconvert_string_array(data, nan_rep=None, encoding=encoding)
+        index = _unconvert_string_array(data, nan_rep=None, encoding=encoding,
+                                        errors=errors)
     elif kind == u('object'):
         index = np.asarray(data[0])
     else:  # pragma: no cover
@@ -4530,20 +4541,22 @@ def _unconvert_index(data, kind, encoding=None):
     return index
 
 
-def _unconvert_index_legacy(data, kind, legacy=False, encoding=None):
+def _unconvert_index_legacy(data, kind, legacy=False, encoding=None,
+                            errors='strict'):
     kind = _ensure_decoded(kind)
     if kind == u('datetime'):
         index = to_datetime(data)
     elif kind in (u('integer')):
         index = np.asarray(data, dtype=object)
     elif kind in (u('string')):
-        index = _unconvert_string_array(data, nan_rep=None, encoding=encoding)
+        index = _unconvert_string_array(data, nan_rep=None, encoding=encoding,
+                                        errors=errors)
     else:  # pragma: no cover
         raise ValueError('unrecognized index type %s' % kind)
     return index
 
 
-def _convert_string_array(data, encoding, itemsize=None, errors='strict'):
+def _convert_string_array(data, encoding, errors, itemsize=None):
     """
     we take a string-like that is object dtype and coerce to a fixed size
     string type
@@ -4552,8 +4565,8 @@ def _convert_string_array(data, encoding, itemsize=None, errors='strict'):
     ----------
     data : a numpy array of object dtype
     encoding : None or string-encoding
+    errors : handler for encoding errors
     itemsize : integer, optional, defaults to the max length of the strings
-    errors : handler for encoding errors, default 'strict'
 
     Returns
     -------
@@ -4616,15 +4629,15 @@ def _unconvert_string_array(data, nan_rep=None, encoding=None, errors='strict'):
     return data.reshape(shape)
 
 
-def _maybe_convert(values, val_kind, encoding, errors='strict'):
+def _maybe_convert(values, val_kind, encoding, errors):
     if _need_convert(val_kind):
-        conv = _get_converter(val_kind, encoding, errors=errors)
+        conv = _get_converter(val_kind, encoding, errors)
         # conv = np.frompyfunc(conv, 1, 1)
         values = conv(values)
     return values
 
 
-def _get_converter(kind, encoding, errors='strict'):
+def _get_converter(kind, encoding, errors):
     kind = _ensure_decoded(kind)
     if kind == 'datetime64':
         return lambda x: np.asarray(x, dtype='M8[ns]')

From 3973ef795dd405a4f82ec22ac879d37d6f73f8c8 Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 23:17:41 -0700
Subject: [PATCH 5/7] Updated whatsnew

---
 doc/source/whatsnew/v0.23.0.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/doc/source/whatsnew/v0.23.0.txt b/doc/source/whatsnew/v0.23.0.txt
index c128058858c17..d9d89993568b7 100644
--- a/doc/source/whatsnew/v0.23.0.txt
+++ b/doc/source/whatsnew/v0.23.0.txt
@@ -450,6 +450,7 @@ Other Enhancements
 - Updated :meth:`DataFrame.to_gbq` and :meth:`pandas.read_gbq` signature and documentation to reflect changes from
   the Pandas-GBQ library version 0.4.0. Adds intersphinx mapping to Pandas-GBQ
   library. (:issue:`20564`)
+- :func:`to_hdf` and :func:`read_hdf` now accept an ``errors`` keyword argument to control encoding error handling (:issue:`20835`)
 
 .. _whatsnew_0230.api_breaking:
 

From 61a0c6b54b0fc762bdc5fb9deb842c309570cc05 Mon Sep 17 00:00:00 2001
From: Will Ayd <william.ayd@icloud.com>
Date: Sun, 29 Apr 2018 23:19:20 -0700
Subject: [PATCH 6/7] LINT fixup

---
 pandas/io/pytables.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 9ac954e6ead06..f27292eec36f2 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -2230,7 +2230,8 @@ class Fixed(StringMixin):
     ndim = None
     is_table = False
 
-    def __init__(self, parent, group, encoding=None, errors='strict', **kwargs):
+    def __init__(self, parent, group, encoding=None, errors='strict',
+                 **kwargs):
         self.parent = parent
         self.group = group
         self.encoding = _ensure_encoding(encoding)
@@ -4587,7 +4588,8 @@ def _convert_string_array(data, encoding, errors, itemsize=None):
     return data
 
 
-def _unconvert_string_array(data, nan_rep=None, encoding=None, errors='strict'):
+def _unconvert_string_array(data, nan_rep=None, encoding=None,
+                            errors='strict'):
     """
     inverse of _convert_string_array
 

From 0fe838afb519dfcaab39f525446ba05ea4789f7f Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Tue, 1 May 2018 06:28:06 -0500
Subject: [PATCH 7/7] Document errors

---
 pandas/core/generic.py | 4 ++++
 pandas/io/pytables.py  | 4 ++++
 2 files changed, 8 insertions(+)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 6d55f92167d3b..31a33c6f464c3 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -1946,6 +1946,10 @@ def to_hdf(self, path_or_buf, key, **kwargs):
             If applying compression use the fletcher32 checksum.
         dropna : bool, default False
             If true, ALL nan rows will not be written to store.
+        errors : str, default 'strict'
+            Specifies how encoding and decoding errors are to be handled.
+            See the errors argument for :func:`open` for a full list
+            of options.
 
         See Also
         --------
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index f27292eec36f2..5b06bca19cf13 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -308,6 +308,10 @@ def read_hdf(path_or_buf, key=None, mode='r', **kwargs):
             return columns
         iterator : optional, boolean, return an iterator, default False
         chunksize : optional, nrows to include in iteration, return an iterator
+        errors : str, default 'strict'
+            Specifies how encoding and decoding errors are to be handled.
+            See the errors argument for :func:`open` for a full list
+            of options.
 
         Returns
         -------