Queria ver os métodos disponíveis para um objeto pandas. Quando executei esse código, recebi um erro AttributeError. Pesquisei, mas não encontrei um exemplo desse erro ou como corrigi-lo.

for i in (df_jobs.groupby(['group', 'failed'])['failed']):
    object_methods = [method_name for method_name in dir(i[1])
                      if callable(getattr(i[1], method_name))]
    break

AttributeError                            Traceback (most recent call last)
<ipython-input-322-70ac95067677> in <module>
     54 #     print(i[1].count())  # YES YES YES
     55 
---> 56     object_methods = [method_name for method_name in dir(i[1])
     57                       if callable(getattr(i[1], method_name))]
     58     break

<ipython-input-322-70ac95067677> in <listcomp>(.0)
     55 
     56     object_methods = [method_name for method_name in dir(i[1])
---> 57                       if callable(getattr(i[1], method_name))]
     58     break
     59 

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   4374             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   4375                 return self[name]
-> 4376             return object.__getattribute__(self, name)
   4377 
   4378     def __setattr__(self, name, value):

~\Anaconda3\lib\site-packages\pandas\core\generic.py in _constructor_sliced(self)
    222         original, such as DataFrame single columns slicing.
    223         """
--> 224         raise com.AbstractMethodError(self)
    225 
    226     @property

AttributeError: module 'pandas.core.common' has no attribute 'AbstractMethodError'

Edita
Aqui está o código para reproduzir uma linha do dataframedf_jobs e saída de amostra:

sample_row = pd.DataFrame([['g1', 'u1', 3902779, '2018-09-27 21:38:06', '2018-10-01 07:24:38', '2018-10-01 08:00:42', 0, 0, 'single', 1, 55696, 609865728.0, 4.0, 6.0, 0, 0, 4.0, 0, 'single', 1, 0, pd.Timedelta('3 days 09:46:32'), pd.Timedelta('00:36:04')]], 
                          columns=['group', 'owner', 'job_number', 'submission_time', 'start_time', 'end_time', 'failed', 'exit_status', 'granted_pe', 'slots', 'task_number', 'maxvmem', 'h_data', 'h_rt', 'highp', 'exclusive', 'h_vmem', 'gpu', 'pe', 'slot', 'campus', 'wait_time', 'wtime'])

sample_row = (sample_row.astype(dtype={'group':'str', 'owner':'str', 'job_number':'int', 'submission_time':'datetime64[ns]', 'start_time':'datetime64[ns]', 'end_time':'datetime64[ns]', 'failed':'int', 'exit_status':'int', 'granted_pe':'str', 'slots':'int', 'task_number':'int', 'maxvmem':'float', 'h_data':'float', 'h_rt':'float', 'highp':'int', 'exclusive':'int', 'h_vmem':'float', 'gpu':'int', 'pe':'str', 'slot':'int', 'campus':'int', 'wait_time':'timedelta64[ns]', 'wtime':'timedelta64[ns]'}))

print(sample_row)

Saída

   group     owner  job_number     submission_time          start_time  \
1  yxing  yidazhan  3902779    2018-09-27 21:38:06 2018-10-01 07:24:38   

             end_time  failed  exit_status granted_pe  slots  task_number  \
1 2018-10-01 08:00:42  0       0            single     1      55696         

       maxvmem  h_data  h_rt  highp  exclusive  h_vmem  gpu      pe  slot  \
1  609865728.0  4.0     6.0   0      0          4.0     0    single  1      

   campus       wait_time    wtime  
1  0      3 days 09:46:32 00:36:04  

Windows 10
Desinstalei / reinstalei o Anaconda esta seman
pandas 0.23.4 py37h830ac7b_0

Informação do servidor
Você está usando o notebook Jupyte

A versão do servidor notebook é: 5.7.4-f6790e4
O servidor está sendo executado nesta versão do Python:
Python 3.7.1 (padrão, 10 de dezembro de 2018, 22:54:23) [MSC v.1915 de 64 bits (AMD64)]

nformações sobre o kernel atual:
Python 3.7.1 (padrão, 10 de dezembro de 2018, 22:54:23) [MSC v.1915 de 64 bits (AMD64)]
IPython 7.2.0 - Um Python Interativo aprimorado. Tipo '?' para ajuda

Edit 2 (16/2/19):

Entrad:

import pandas as pd

df_jobs = pd.DataFrame([['g1', 'u1', 3902779, '2018-09-27 21:38:06', '2018-10-01 07:24:38', '2018-10-01 08:00:42', 0, 0, 'single', 1, 55696, 609865728.0, 4.0, 6.0, 0, 0, 4.0, 0, 'single', 1, 0, pd.Timedelta('3 days 09:46:32'), pd.Timedelta('00:36:04')]], 
                          columns=['group', 'owner', 'job_number', 'submission_time', 'start_time', 'end_time', 'failed', 'exit_status', 'granted_pe', 'slots', 'task_number', 'maxvmem', 'h_data', 'h_rt', 'highp', 'exclusive', 'h_vmem', 'gpu', 'pe', 'slot', 'campus', 'wait_time', 'wtime'])

df_jobs = (df_jobs.astype(dtype={'group':'str', 'owner':'str', 'job_number':'int', 'submission_time':'datetime64[ns]', 'start_time':'datetime64[ns]', 'end_time':'datetime64[ns]', 'failed':'int', 'exit_status':'int', 'granted_pe':'str', 'slots':'int', 'task_number':'int', 'maxvmem':'float', 'h_data':'float', 'h_rt':'float', 'highp':'int', 'exclusive':'int', 'h_vmem':'float', 'gpu':'int', 'pe':'str', 'slot':'int', 'campus':'int', 'wait_time':'timedelta64[ns]', 'wtime':'timedelta64[ns]'}))

grouped_df_jobs = df_jobs.groupby(['group', 'failed'])

for params, table in grouped_df_jobs:
    object_methods_params = [method_name for method_name in dir(params)
                             if callable(getattr(params, method_name))]
    print('params:', str(params), '\n\nparams methods:\n', object_methods_params, '\n')

    object_methods_table  = [method_name for method_name in dir(table)
                             if callable(getattr(table, method_name))]
    print('table:\n', str(table), '\n\ntable methods:\n', object_methods_table, '\n')

    for index, row in table.iterrows():
        object_methods_index = [method_name for method_name in dir(index)
                         if callable(getattr(index, method_name))]
        print('index:', str(index), '\n\ntable index methods:\n', object_methods_index, '\n')

        object_methods_row  = [method_name for method_name in dir(row)
                                 if callable(getattr(row, method_name))]        
        print('row:\n', str(row), '\n\ntable row methods:\n', object_methods_row)

    break

Saíd:

params: ('aaamini', 37) 

params methods:
 ['__add__', '__class__', '__contains__', '__delattr__', '__dir__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getnewargs__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__iter__', '__le__', '__len__', '__lt__', '__mul__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__rmul__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'count', 'index'] 

table:
           group     owner  job_number     submission_time          start_time  \
412327  aaamini  sjalilkt  3939911    2018-10-04 06:16:57 2018-10-04 06:17:49   

                  end_time  failed  exit_status granted_pe  slots  \
412327 2018-10-04 08:20:02  37      0            single     1       

        task_number  maxvmem  h_data  h_rt  highp  exclusive  h_vmem  gpu  \
412327  0            0.0      4.0     2.0   0      0          0.0     0     

            pe  slot  campus wait_time    wtime  
412327  single  1     1      00:00:52  02:02:13   

table methods:
 ['__abs__', '__add__', '__and__', '__array__', '__array_wrap__', '__bool__', '__bytes__', '__class__', '__contains__', '__copy__', '__deepcopy__', '__delattr__', '__delitem__', '__dir__', '__div__', '__eq__', '__finalize__', '__floordiv__', '__format__', '__ge__', '__getattr__', '__getattribute__', '__getitem__', '__getstate__', '__gt__', '__hash__', '__iadd__', '__iand__', '__ifloordiv__', '__imod__', '__imul__', '__init__', '__init_subclass__', '__invert__', '__ior__', '__ipow__', '__isub__', '__iter__', '__itruediv__', '__ixor__', '__le__', '__len__', '__lt__', '__matmul__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__nonzero__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__rdiv__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rmatmul__', '__rmod__', '__rmul__', '__ror__', '__round__', '__rpow__', '__rsub__', '__rtruediv__', '__rxor__', '__setattr__', '__setitem__', '__setstate__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__unicode__', '__xor__', '_add_numeric_operations', '_add_series_only_operations', '_add_series_or_dataframe_operations', '_agg_by_level', '_aggregate', '_aggregate_multiple_funcs', '_align_frame', '_align_series', '_box_col_values', '_box_item_values', '_check_inplace_setting', '_check_is_chained_assignment_possible', '_check_label_or_level_ambiguity', '_check_percentile', '_check_setitem_copy', '_clear_item_cache', '_clip_with_one_bound', '_clip_with_scalar', '_combine_const', '_combine_frame', '_combine_match_columns', '_combine_match_index', '_compare_frame', '_consolidate', '_consolidate_inplace', '_construct_axes_dict', '_construct_axes_dict_for_slice', '_construct_axes_dict_from', '_construct_axes_from_arguments', '_constructor', '_constructor_expanddim', '_constructor_sliced', '_convert', '_count_level', '_create_indexer', '_dir_additions', '_dir_deletions', '_drop_axis', '_drop_labels_or_levels', '_ensure_valid_index', '_expand_axes', '_find_valid_index', '_from_arrays', '_from_axes', '_get_agg_axis', '_get_axis', '_get_axis_name', '_get_axis_number', '_get_axis_resolvers', '_get_block_manager_axis', '_get_bool_data', '_get_cacher', '_get_index_resolvers', '_get_item_cache', '_get_label_or_level_values', '_get_numeric_data', '_get_value', '_getitem_array', '_getitem_column', '_getitem_frame', '_getitem_multilevel', '_getitem_slice', '_gotitem', '_iget_item_cache', '_indexed_same', '_info_repr', '_init_dict', '_init_mgr', '_init_ndarray', '_is_builtin_func', '_is_copy', '_is_cython_func', '_is_label_or_level_reference', '_is_label_reference', '_is_level_reference', '_ixs', '_join_compat', '_maybe_cache_changed', '_maybe_update_cacher', '_needs_reindex_multi', '_protect_consolidate', '_reduce', '_reindex_axes', '_reindex_axis', '_reindex_columns', '_reindex_index', '_reindex_multi', '_reindex_with_indexers', '_repr_data_resource_', '_repr_fits_horizontal_', '_repr_fits_vertical_', '_repr_html_', '_repr_latex_', '_reset_cache', '_reset_cacher', '_sanitize_column', '_set_as_cached', '_set_axis', '_set_axis_name', '_set_is_copy', '_set_item', '_set_value', '_setitem_array', '_setitem_frame', '_setitem_slice', '_setup_axes', '_shallow_copy', '_slice', '_take', '_to_dict_of_blocks', '_try_aggregate_string_function', '_unpickle_frame_compat', '_unpickle_matrix_compat', '_update_inplace', '_validate_dtype', '_where', '_xs', 'abs', 'add', 'add_prefix', 'add_suffix', 'agg', 'aggregate', 'align', 'all', 'any', 'append', 'apply', 'applymap', 'as_matrix', 'asfreq', 'asof', 'assign', 'astype', 'at', 'at_time', 'between_time', 'bfill', 'bool', 'boxplot', 'clip', 'clip_lower', 'clip_upper', 'combine', 'combine_first', 'compound', 'copy', 'corr', 'corrwith', 'count', 'cov', 'cummax', 'cummin', 'cumprod', 'cumsum', 'describe', 'diff', 'div', 'divide', 'dot', 'drop', 'drop_duplicates', 'dropna', 'duplicated', 'eq', 'equals', 'eval', 'ewm', 'expanding', 'ffill', 'fillna', 'filter', 'first', 'first_valid_index', 'floordiv', 'from_dict', 'from_records', 'ge', 'get', 'get_dtype_counts', 'get_ftype_counts', 'get_values', 'groupby', 'gt', 'head', 'hist', 'iat', 'idxmax', 'idxmin', 'iloc', 'infer_objects', 'info', 'insert', 'interpolate', 'isin', 'isna', 'isnull', 'items', 'iteritems', 'iterrows', 'itertuples', 'ix', 'join', 'keys', 'kurt', 'kurtosis', 'last', 'last_valid_index', 'le', 'loc', 'lookup', 'lt', 'mad', 'mask', 'max', 'mean', 'median', 'melt', 'memory_usage', 'merge', 'min', 'mod', 'mode', 'mul', 'multiply', 'ne', 'nlargest', 'notna', 'notnull', 'nsmallest', 'nunique', 'pct_change', 'pipe', 'pivot', 'pivot_table', 'plot', 'pop', 'pow', 'prod', 'product', 'quantile', 'query', 'radd', 'rank', 'rdiv', 'reindex', 'reindex_axis', 'reindex_like', 'rename', 'rename_axis', 'reorder_levels', 'replace', 'resample', 'reset_index', 'rfloordiv', 'rmod', 'rmul', 'rolling', 'round', 'rpow', 'rsub', 'rtruediv', 'sample', 'select', 'select_dtypes', 'sem', 'set_axis', 'set_index', 'shift', 'skew', 'slice_shift', 'sort_index', 'sort_values', 'squeeze', 'stack', 'std', 'sub', 'subtract', 'sum', 'swapaxes', 'swaplevel', 'tail', 'take', 'to_clipboard', 'to_csv', 'to_dense', 'to_dict', 'to_excel', 'to_feather', 'to_gbq', 'to_hdf', 'to_html', 'to_json', 'to_latex', 'to_msgpack', 'to_panel', 'to_parquet', 'to_period', 'to_pickle', 'to_records', 'to_sparse', 'to_sql', 'to_stata', 'to_string', 'to_timestamp', 'to_xarray', 'transform', 'transpose', 'truediv', 'truncate', 'tshift', 'tz_convert', 'tz_localize', 'unstack', 'update', 'var', 'where', 'xs'] 

index: 412327 

table index methods:
 ['__abs__', '__add__', '__and__', '__bool__', '__ceil__', '__class__', '__delattr__', '__dir__', '__divmod__', '__eq__', '__float__', '__floor__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__getnewargs__', '__gt__', '__hash__', '__index__', '__init__', '__init_subclass__', '__int__', '__invert__', '__le__', '__lshift__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rlshift__', '__rmod__', '__rmul__', '__ror__', '__round__', '__rpow__', '__rrshift__', '__rshift__', '__rsub__', '__rtruediv__', '__rxor__', '__setattr__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__trunc__', '__xor__', 'bit_length', 'conjugate', 'from_bytes', 'to_bytes'] 

C:\Users\karls\Anaconda3\lib\site-packages\ipykernel_launcher.py:77: DeprecationWarning: 
.ix is deprecated. Please use
.loc for label based indexing or
.iloc for positional indexing

See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-463-513651be1e59> in <module>
     83         print('index:', str(index), '\n\ntable index methods:\n', object_methods_index, '\n')
     84 
---> 85         object_methods_row  = [method_name for method_name in dir(row)
     86                                  if callable(getattr(row, method_name))]        
     87         print('row:\n', str(row), '\n\ntable row methods:\n', object_methods_row)

<ipython-input-463-513651be1e59> in <listcomp>(.0)
     84 
     85         object_methods_row  = [method_name for method_name in dir(row)
---> 86                                  if callable(getattr(row, method_name))]        
     87         print('row:\n', str(row), '\n\ntable row methods:\n', object_methods_row)
     88 

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   4374             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   4375                 return self[name]
-> 4376             return object.__getattribute__(self, name)
   4377 
   4378     def __setattr__(self, name, value):

~\Anaconda3\lib\site-packages\pandas\core\generic.py in _constructor_sliced(self)
    222         original, such as DataFrame single columns slicing.
    223         """
--> 224         raise com.AbstractMethodError(self)
    225 
    226     @property

AttributeError: module 'pandas.core.common' has no attribute 'AbstractMethodError'