Pandas gives 600 line long ValueError while runing sklearn GridSearchCV
I am using sklearn GridSearchCV to classify some data. When I run this code, pandas gives 600 line long error. If I set n_jobs=1, it runs fine without any error. Please kindly take a look at it. Thanks

```
rfc = RandomForestClassifier(random_state=1)
tuned_parameters = [{'max_features': ['sqrt', 'log2'], 
                 'n_estimators': [20, 100, 200, 500, 1000]}]

clf = GridSearchCV(rfc, tuned_parameters, scoring='roc_auc', cv=3, n_jobs=-1, verbose=2)
clf.fit(X, y)
```

Error message

```
Fitting 3 folds for each of 10 candidates, totalling 30 fits
[CV] max_features=sqrt, n_estimators=20 ..............................
[CV] max_features=sqrt, n_estimators=20 ..............................
[CV] max_features=sqrt, n_estimators=20 ..............................
[CV] max_features=sqrt, n_estimators=100 .............................
An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (101150, 0))
An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (101150, 0))
An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (101150, 0))
An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (101150, 0))




[CV] max_features=sqrt, n_estimators=200 .............................[CV] max_features=sqrt, n_estimators=100 .............................[CV] max_features=sqrt, n_estimators=100 .............................[CV] max_features=sqrt, n_estimators=200 .............................



---------------------------------------------------------------------------
JoblibValueError                          Traceback (most recent call last)
<ipython-input-25-99a52d0f19db> in <module>()
4
      5 clf = GridSearchCV(rfc, tuned_parameters, scoring='roc_auc', cv=3, n_jobs=-1, verbose=2)
----> 6 clf.fit(X, y)

/home/user/anaconda/lib/python2.7/site-packages/sklearn/grid_search.pyc in fit(self, X, y)
730
    731         """
--> 732         return self._fit(X, y, ParameterGrid(self.param_grid))
733
734

/home/user/anaconda/lib/python2.7/site-packages/sklearn/grid_search.pyc in _fit(self, X, y, parameter_iterable)
    503                                     self.fit_params, return_parameters=True,
    504                                     error_score=self.error_score)
--> 505                 for parameters in parameter_iterable
    506                 for train, test in cv)
507

/home/user/anaconda/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc in __call__(self, iterable)
    664                 # consumption.
    665                 self._iterating = False
--> 666             self.retrieve()
    667             # Make sure that we get a last message telling us we are done
    668             elapsed_time = time.time() - self._start_time

/home/user/anaconda/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.pyc in retrieve(self)
    547                         # Convert this to a JoblibException
    548                         exception_type = _mk_exception(exception.etype)[0]
--> 549                         raise exception_type(report)
    550                     raise exception
    551                 finally:

JoblibValueError: JoblibValueError
___________________________________________________________________________
Multiprocessing exception:
    ...........................................................................
/home/user/anaconda/lib/python2.7/runpy.py in _run_module_as_main(mod_name='IPython.kernel.__main__', alter_argv=1)
    157     pkg_name = mod_name.rpartition('.')[0]
    158     main_globals = sys.modules["__main__"].__dict__
    159     if alter_argv:
    160         sys.argv[0] = fname
    161     return _run_code(code, main_globals, None,
--> 162                      "__main__", fname, loader, pkg_name)
        fname = '/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py'
        loader = <pkgutil.ImpLoader instance>
        pkg_name = 'IPython.kernel'
163
    164 def run_module(mod_name, init_globals=None,
    165                run_name=None, alter_sys=False):
    166     """Execute a module's code without importing it

...........................................................................
/home/user/anaconda/lib/python2.7/runpy.py in _run_code(code=<code object <module> at 0x7f8c57a1c630, file "/...ite-packages/IPython/kernel/__main__.py", line 1>, run_globals={'__builtins__': <module '__builtin__' (built-in)>, '__doc__': None, '__file__': '/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py', '__loader__': <pkgutil.ImpLoader instance>, '__name__': '__main__', '__package__': 'IPython.kernel', 'app': <module 'IPython.kernel.zmq.kernelapp' from '/ho.../site-packages/IPython/kernel/zmq/kernelapp.pyc'>}, init_globals=None, mod_name='__main__', mod_fname='/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py', mod_loader=<pkgutil.ImpLoader instance>, pkg_name='IPython.kernel')
     67         run_globals.update(init_globals)
     68     run_globals.update(__name__ = mod_name,
     69                        __file__ = mod_fname,
     70                        __loader__ = mod_loader,
     71                        __package__ = pkg_name)
---> 72     exec code in run_globals
        code = <code object <module> at 0x7f8c57a1c630, file "/...ite-packages/IPython/kernel/__main__.py", line 1>
        run_globals = {'__builtins__': <module '__builtin__' (built-in)>, '__doc__': None, '__file__': '/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py', '__loader__': <pkgutil.ImpLoader instance>, '__name__': '__main__', '__package__': 'IPython.kernel', 'app': <module 'IPython.kernel.zmq.kernelapp' from '/ho.../site-packages/IPython/kernel/zmq/kernelapp.pyc'>}
     73     return run_globals
74
     75 def _run_module_code(code, init_globals=None,
     76                     mod_name=None, mod_fname=None,

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/__main__.py in <module>()
1
2
----> 3 
      4 if __name__ == '__main__':
      5     from IPython.kernel.zmq import kernelapp as app
      6     app.launch_new_instance()
7
8
9
10

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/config/application.py in launch_instance(cls=<class 'IPython.kernel.zmq.kernelapp.IPKernelApp'>, argv=None, **kwargs={})
569
    570         If a global instance already exists, this reinitializes and starts it
    571         """
    572         app = cls.instance(**kwargs)
    573         app.initialize(argv)
--> 574         app.start()
        app.start = <bound method IPKernelApp.start of <IPython.kernel.zmq.kernelapp.IPKernelApp object>>
575
    576 #-----------------------------------------------------------------------------
    577 # utility functions, for convenience
    578 #-----------------------------------------------------------------------------

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/zmq/kernelapp.py in start(self=<IPython.kernel.zmq.kernelapp.IPKernelApp object>)
    368     def start(self):
    369         if self.poller is not None:
    370             self.poller.start()
    371         self.kernel.start()
    372         try:
--> 373             ioloop.IOLoop.instance().start()
    374         except KeyboardInterrupt:
    375             pass
376
    377 launch_new_instance = IPKernelApp.launch_instance

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/zmq/eventloop/ioloop.py in start(self=<zmq.eventloop.ioloop.ZMQIOLoop object>)
    146             PollIOLoop.configure(ZMQIOLoop)
    147         return PollIOLoop.instance()
148
    149     def start(self):
    150         try:
--> 151             super(ZMQIOLoop, self).start()
        self.start = <bound method ZMQIOLoop.start of <zmq.eventloop.ioloop.ZMQIOLoop object>>
    152         except ZMQError as e:
    153             if e.errno == ETERM:
    154                 # quietly return on ETERM
    155                 pass

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/tornado/ioloop.py in start(self=<zmq.eventloop.ioloop.ZMQIOLoop object>)
    835                 self._events.update(event_pairs)
    836                 while self._events:
    837                     fd, events = self._events.popitem()
    838                     try:
    839                         fd_obj, handler_func = self._handlers[fd]
--> 840                         handler_func(fd_obj, events)
        handler_func = <function null_wrapper>
        fd_obj = <zmq.sugar.socket.Socket object>
        events = 5
    841                     except (OSError, IOError) as e:
    842                         if errno_from_exception(e) == errno.EPIPE:
    843                             # Happens when the client closes the connection
    844                             pass

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/tornado/stack_context.py in null_wrapper(*args=(<zmq.sugar.socket.Socket object>, 5), **kwargs={})
    270         # Fast path when there are no active contexts.
    271         def null_wrapper(*args, **kwargs):
    272             try:
    273                 current_state = _state.contexts
    274                 _state.contexts = cap_contexts[0]
--> 275                 return fn(*args, **kwargs)
        args = (<zmq.sugar.socket.Socket object>, 5)
        kwargs = {}
    276             finally:
    277                 _state.contexts = current_state
    278         null_wrapper._wrapped = True
    279         return null_wrapper

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py in _handle_events(self=<zmq.eventloop.zmqstream.ZMQStream object>, fd=<zmq.sugar.socket.Socket object>, events=5)
    428             # dispatch events:
    429             if events & IOLoop.ERROR:
    430                 gen_log.error("got POLLERR event on ZMQStream, which doesn't make sense")
    431                 return
    432             if events & IOLoop.READ:
--> 433                 self._handle_recv()
        self._handle_recv = <bound method ZMQStream._handle_recv of <zmq.eventloop.zmqstream.ZMQStream object>>
    434                 if not self.socket:
    435                     return
    436             if events & IOLoop.WRITE:
    437                 self._handle_send()

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py in _handle_recv(self=<zmq.eventloop.zmqstream.ZMQStream object>)
    460                 gen_log.error("RECV Error: %s"%zmq.strerror(e.errno))
    461         else:
    462             if self._recv_callback:
    463                 callback = self._recv_callback
    464                 # self._recv_callback = None
--> 465                 self._run_callback(callback, msg)
        self._run_callback = <bound method ZMQStream._run_callback of <zmq.eventloop.zmqstream.ZMQStream object>>
        callback = <function null_wrapper>
        msg = [<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>]
466
    467         # self.update_state()
468
469

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py in _run_callback(self=<zmq.eventloop.zmqstream.ZMQStream object>, callback=<function null_wrapper>, *args=([<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>],), **kwargs={})
    402         close our socket."""
    403         try:
    404             # Use a NullContext to ensure that all StackContexts are run
    405             # inside our blanket exception handler rather than outside.
    406             with stack_context.NullContext():
--> 407                 callback(*args, **kwargs)
        callback = <function null_wrapper>
        args = ([<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>],)
        kwargs = {}
    408         except:
    409             gen_log.error("Uncaught exception, closing connection.",
    410                           exc_info=True)
    411             # Close the socket on an uncaught exception from a user callback

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/tornado/stack_context.py in null_wrapper(*args=([<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>],), **kwargs={})
    270         # Fast path when there are no active contexts.
    271         def null_wrapper(*args, **kwargs):
    272             try:
    273                 current_state = _state.contexts
    274                 _state.contexts = cap_contexts[0]
--> 275                 return fn(*args, **kwargs)
        args = ([<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>],)
        kwargs = {}
    276             finally:
    277                 _state.contexts = current_state
    278         null_wrapper._wrapped = True
    279         return null_wrapper

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/zmq/kernelbase.py in dispatcher(msg=[<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>])
    247         if self.control_stream:
    248             self.control_stream.on_recv(self.dispatch_control, copy=False)
249
    250         def make_dispatcher(stream):
    251             def dispatcher(msg):
--> 252                 return self.dispatch_shell(stream, msg)
        msg = [<zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>, <zmq.sugar.frame.Frame object>]
    253             return dispatcher
254
    255         for s in self.shell_streams:
    256             s.on_recv(make_dispatcher(s), copy=False)

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/zmq/kernelbase.py in dispatch_shell(self=<IPython.kernel.zmq.ipkernel.IPythonKernel object>, stream=<zmq.eventloop.zmqstream.ZMQStream object>, msg={'buffers': [], 'content': {u'allow_stdin': True, u'code': u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)", u'silent': False, u'stop_on_error': True, u'store_history': True, u'user_expressions': {}}, 'header': {u'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', u'msg_type': u'execute_request', u'session': u'D2F6FC266E4F453AB36721F7AF6CAD31', u'username': u'username', u'version': u'5.0'}, 'metadata': {}, 'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', 'msg_type': u'execute_request', 'parent_header': {}})
    208         else:
    209             # ensure default_int_handler during handler call
    210             sig = signal(SIGINT, default_int_handler)
    211             self.log.debug("%s: %s", msg_type, msg)
    212             try:
--> 213                 handler(stream, idents, msg)
        handler = <bound method IPythonKernel.execute_request of <IPython.kernel.zmq.ipkernel.IPythonKernel object>>
        stream = <zmq.eventloop.zmqstream.ZMQStream object>
        idents = ['D2F6FC266E4F453AB36721F7AF6CAD31']
        msg = {'buffers': [], 'content': {u'allow_stdin': True, u'code': u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)", u'silent': False, u'stop_on_error': True, u'store_history': True, u'user_expressions': {}}, 'header': {u'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', u'msg_type': u'execute_request', u'session': u'D2F6FC266E4F453AB36721F7AF6CAD31', u'username': u'username', u'version': u'5.0'}, 'metadata': {}, 'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', 'msg_type': u'execute_request', 'parent_header': {}}
    214             except Exception:
    215                 self.log.error("Exception in message handler:", exc_info=True)
    216             finally:
    217                 signal(SIGINT, sig)

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/zmq/kernelbase.py in execute_request(self=<IPython.kernel.zmq.ipkernel.IPythonKernel object>, stream=<zmq.eventloop.zmqstream.ZMQStream object>, ident=['D2F6FC266E4F453AB36721F7AF6CAD31'], parent={'buffers': [], 'content': {u'allow_stdin': True, u'code': u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)", u'silent': False, u'stop_on_error': True, u'store_history': True, u'user_expressions': {}}, 'header': {u'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', u'msg_type': u'execute_request', u'session': u'D2F6FC266E4F453AB36721F7AF6CAD31', u'username': u'username', u'version': u'5.0'}, 'metadata': {}, 'msg_id': u'122E08A036D8493A821D16CB2F4EE32A', 'msg_type': u'execute_request', 'parent_header': {}})
    357         if not silent:
    358             self.execution_count += 1
    359             self._publish_execute_input(code, parent, self.execution_count)
360
    361         reply_content = self.do_execute(code, silent, store_history,
--> 362                                         user_expressions, allow_stdin)
        user_expressions = {}
        allow_stdin = True
363
    364         # Flush output before sending the reply.
    365         sys.stdout.flush()
    366         sys.stderr.flush()

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/kernel/zmq/ipkernel.py in do_execute(self=<IPython.kernel.zmq.ipkernel.IPythonKernel object>, code=u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)", silent=False, store_history=True, user_expressions={}, allow_stdin=True)
176
    177         reply_content = {}
    178         # FIXME: the shell calls the exception handler itself.
    179         shell._reply_content = None
    180         try:
--> 181             shell.run_cell(code, store_history=store_history, silent=silent)
        shell.run_cell = <bound method ZMQInteractiveShell.run_cell of <I....kernel.zmq.zmqshell.ZMQInteractiveShell object>>
        code = u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)"
        store_history = True
        silent = False
    182         except:
    183             status = u'error'
    184             # FIXME: this code right now isn't being used yet by default,
    185             # because the run_cell() call above directly fires off exception

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py in run_cell(self=<IPython.kernel.zmq.zmqshell.ZMQInteractiveShell object>, raw_cell=u"rfc = RandomForestClassifier(random_state=1)\n...auc', cv=3, n_jobs=-1, verbose=2)\nclf.fit(X, y)", store_history=True, silent=False, shell_futures=True)
   2866                 self.displayhook.exec_result = result
2867
   2868                 # Execute the user code
   2869                 interactivity = "none" if silent else self.ast_node_interactivity
   2870                 self.run_ast_nodes(code_ast.body, cell_name,
-> 2871                    interactivity=interactivity, compiler=compiler, result=result)
        interactivity = 'last_expr'
        compiler = <IPython.core.compilerop.CachingCompiler instance>
2872
   2873                 # Reset this so later displayed values do not modify the
   2874                 # ExecutionResult
   2875                 self.displayhook.exec_result = None

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py in run_ast_nodes(self=<IPython.kernel.zmq.zmqshell.ZMQInteractiveShell object>, nodelist=[<_ast.Assign object>, <_ast.Assign object>, <_ast.Assign object>, <_ast.Expr object>], cell_name='<ipython-input-25-99a52d0f19db>', interactivity='last', compiler=<IPython.core.compilerop.CachingCompiler instance>, result=<IPython.core.interactiveshell.ExecutionResult object>)
   2976                     return True
2977
   2978             for i, node in enumerate(to_run_interactive):
   2979                 mod = ast.Interactive([node])
   2980                 code = compiler(mod, cell_name, "single")
-> 2981                 if self.run_code(code, result):
        self.run_code = <bound method ZMQInteractiveShell.run_code of <I....kernel.zmq.zmqshell.ZMQInteractiveShell object>>
        code = <code object <module> at 0x7f8c215a43b0, file "<ipython-input-25-99a52d0f19db>", line 6>
        result = <IPython.core.interactiveshell.ExecutionResult object>
   2982                     return True
2983
   2984             # Flush softspace
   2985             if softspace(sys.stdout, 0):

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py in run_code(self=<IPython.kernel.zmq.zmqshell.ZMQInteractiveShell object>, code_obj=<code object <module> at 0x7f8c215a43b0, file "<ipython-input-25-99a52d0f19db>", line 6>, result=<IPython.core.interactiveshell.ExecutionResult object>)
   3030         outflag = 1  # happens in more places, so it's easier as default
   3031         try:
   3032             try:
   3033                 self.hooks.pre_run_code_hook()
   3034                 #rprint('Running code', repr(code_obj)) # dbg
-> 3035                 exec(code_obj, self.user_global_ns, self.user_ns)
        code_obj = <code object <module> at 0x7f8c215a43b0, file "<ipython-input-25-99a52d0f19db>", line 6>
        self.user_global_ns = {'ALLOW_THREADS': 1, 'Annotation': <class 'matplotlib.text.Annotation'>, 'Arrow': <class 'matplotlib.patches.Arrow'>, 'Artist': <class 'matplotlib.artist.Artist'>, 'AutoLocator': <class 'matplotlib.ticker.AutoLocator'>, 'Axes': <class 'matplotlib.axes._axes.Axes'>, 'BUFSIZE': 8192, 'Button': <class 'matplotlib.widgets.Button'>, 'CLIP': 0, 'Circle': <class 'matplotlib.patches.Circle'>, ...}
        self.user_ns = {'ALLOW_THREADS': 1, 'Annotation': <class 'matplotlib.text.Annotation'>, 'Arrow': <class 'matplotlib.patches.Arrow'>, 'Artist': <class 'matplotlib.artist.Artist'>, 'AutoLocator': <class 'matplotlib.ticker.AutoLocator'>, 'Axes': <class 'matplotlib.axes._axes.Axes'>, 'BUFSIZE': 8192, 'Button': <class 'matplotlib.widgets.Button'>, 'CLIP': 0, 'Circle': <class 'matplotlib.patches.Circle'>, ...}
   3036             finally:
   3037                 # Reset our crash handler in place
   3038                 sys.excepthook = old_excepthook
   3039         except SystemExit as e:

...........................................................................
/home/user/data-analysis/GA/project/final/<ipython-input-25-99a52d0f19db> in <module>()
      1 rfc = RandomForestClassifier(random_state=1)
      2 tuned_parameters = [{'max_features': ['sqrt', 'log2'], 
      3                      'n_estimators': [20, 100, 200, 500, 1000]}]
4
      5 clf = GridSearchCV(rfc, tuned_parameters, scoring='roc_auc', cv=3, n_jobs=-1, verbose=2)
----> 6 clf.fit(X, y)
7
8
9
10

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/grid_search.py in fit(self=GridSearchCV(cv=3, error_score='raise',
       e...e_func=None,
       scoring='roc_auc', verbose=2), X=      1516 Quinoa Weisse  18th Street / Against ...0  0.000000      0  

[20000 rows x 5814 columns], y=0       False
0        True
1       False
1     ...lse
9999     True
Name: is_five_star, dtype: bool)
    727         y : array-like, shape = [n_samples] or [n_samples, n_output], optional
    728             Target relative to X for classification or regression;
    729             None for unsupervised learning.
730
    731         """
--> 732         return self._fit(X, y, ParameterGrid(self.param_grid))
        self._fit = <bound method GridSearchCV._fit of GridSearchCV(..._func=None,
       scoring='roc_auc', verbose=2)>
        X =       1516 Quinoa Weisse  18th Street / Against ...0  0.000000      0  

[20000 rows x 5814 columns]
        y = 0       False
0        True
1       False
1     ...lse
9999     True
Name: is_five_star, dtype: bool
        self.param_grid = [{'max_features': ['sqrt', 'log2'], 'n_estimators': [20, 100, 200, 500, 1000]}]
733
734
    735 class RandomizedSearchCV(BaseSearchCV):
    736     """Randomized search on hyper parameters.

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/grid_search.py in _fit(self=GridSearchCV(cv=3, error_score='raise',
       e...e_func=None,
       scoring='roc_auc', verbose=2), X=      1516 Quinoa Weisse  18th Street / Against ...0  0.000000      0  

[20000 rows x 5814 columns], y=0       False
0        True
1       False
1     ...lse
9999     True
Name: is_five_star, dtype: bool, parameter_iterable=<sklearn.grid_search.ParameterGrid object>)
    500         )(
    501             delayed(_fit_and_score)(clone(base_estimator), X, y, self.scorer_,
    502                                     train, test, self.verbose, parameters,
    503                                     self.fit_params, return_parameters=True,
    504                                     error_score=self.error_score)
--> 505                 for parameters in parameter_iterable
        parameters = undefined
        parameter_iterable = <sklearn.grid_search.ParameterGrid object>
    506                 for train, test in cv)
507
    508         # Out is a list of triplet: score, estimator, n_test_samples
    509         n_fits = len(out)

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py in __call__(self=Parallel(n_jobs=-1), iterable=<itertools.islice object>)
    661             if pre_dispatch == "all" or n_jobs == 1:
    662                 # The iterable was consumed all at once by the above for loop.
    663                 # No need to wait for async callbacks to trigger to
    664                 # consumption.
    665                 self._iterating = False
--> 666             self.retrieve()
        self.retrieve = <bound method Parallel.retrieve of Parallel(n_jobs=-1)>
    667             # Make sure that we get a last message telling us we are done
    668             elapsed_time = time.time() - self._start_time
    669             self._print('Done %3i out of %3i | elapsed: %s finished',
    670                         (len(self._output),

    ---------------------------------------------------------------------------
    Sub-process traceback:
    ---------------------------------------------------------------------------
    ValueError                                         Fri Apr 17 23:31:01 2015
PID: 25128                    Python 2.7.9: /home/user/anaconda/bin/python
...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/cross_validation.pyc in _fit_and_score(estimator=RandomForestClassifier(bootstrap=True, class_wei...lse, random_state=1, verbose=0, warm_start=False), X=<class 'pandas.core.frame.DataFrame'> instance, y=0       False
0        True
1       False
1     ...lse
9999     True
Name: is_five_star, dtype: bool, scorer=make_scorer(roc_auc_score, needs_threshold=True), train=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), test=array([   0,    1,    2, ..., 6723, 6725, 6729]), verbose=2, parameters={'max_features': 'sqrt', 'n_estimators': 20}, fit_params={}, return_train_score=False, return_parameters=True, error_score='raise')
   1447     if parameters is not None:
   1448         estimator.set_params(**parameters)
1449
   1450     start_time = time.time()
1451
-> 1452     X_train, y_train = _safe_split(estimator, X, y, train)
   1453     X_test, y_test = _safe_split(estimator, X, y, test, train)
1454
   1455     try:
   1456         if y_train is None:

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/cross_validation.pyc in _safe_split(estimator=RandomForestClassifier(bootstrap=True, class_wei...lse, random_state=1, verbose=0, warm_start=False), X=<class 'pandas.core.frame.DataFrame'> instance, y=0       False
0        True
1       False
1     ...lse
9999     True
Name: is_five_star, dtype: bool, indices=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), train_indices=None)
   1514             if train_indices is None:
   1515                 X_subset = X[np.ix_(indices, indices)]
   1516             else:
   1517                 X_subset = X[np.ix_(indices, train_indices)]
   1518         else:
-> 1519             X_subset = safe_indexing(X, indices)
1520
   1521     if y is not None:
   1522         y_subset = safe_indexing(y, indices)
   1523     else:

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/sklearn/utils/__init__.pyc in safe_indexing(X=<class 'pandas.core.frame.DataFrame'> instance, indices=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]))
    147     indices : array-like, list
    148         Indices according to which X will be subsampled.
    149     """
    150     if hasattr(X, "iloc"):
    151         # Pandas Dataframes and Series
--> 152         return X.iloc[indices]
    153     elif hasattr(X, "shape"):
    154         if hasattr(X, 'take') and (hasattr(indices, 'dtype') and
    155                                    indices.dtype.kind == 'i'):
    156             # This is often substantially faster than X[indices]

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/indexing.pyc in __getitem__(self=<pandas.core.indexing._iLocIndexer object>, key=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]))
1212
   1213     def __getitem__(self, key):
   1214         if type(key) is tuple:
   1215             return self._getitem_tuple(key)
   1216         else:
-> 1217             return self._getitem_axis(key, axis=0)
1218
   1219     def _getitem_axis(self, key, axis=0):
   1220         raise NotImplementedError()
1221

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/indexing.pyc in _getitem_axis(self=<pandas.core.indexing._iLocIndexer object>, key=[6634, 6636, 6638, 6639, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6653, 6654, 6655, 6656, 6658, 6659, 6660, 6662, 6663, ...], axis=0)
   1503                                     "non-integer key")
1504
   1505                 # validate the location
   1506                 self._is_valid_integer(key, axis)
1507
-> 1508             return self._get_loc(key, axis=axis)
1509
   1510     def _convert_to_indexer(self, obj, axis=0, is_setter=False):
   1511         """ much simpler as we only have to deal with our valid types """
1512

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/indexing.pyc in _get_loc(self=<pandas.core.indexing._iLocIndexer object>, key=[6634, 6636, 6638, 6639, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6653, 6654, 6655, 6656, 6658, 6659, 6660, 6662, 6663, ...], axis=0)
     87             raise IndexingError('no slices here, handle elsewhere')
88
     89         return self.obj._xs(label, axis=axis)
90
     91     def _get_loc(self, key, axis=0):
---> 92         return self.obj._ixs(key, axis=axis)
93
     94     def _slice(self, obj, axis=0, kind=None):
     95         return self.obj._slice(obj, axis=axis, kind=kind)
96

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc in _ixs(self=<class 'pandas.core.frame.DataFrame'> instance, i=[6634, 6636, 6638, 6639, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6653, 6654, 6655, 6656, 6658, 6659, 6660, 6662, 6663, ...], axis=0)
   1709                 return self[i]
   1710             else:
   1711                 label = self.index[i]
   1712                 if isinstance(label, Index):
   1713                     # a location index by definition
-> 1714                     result = self.take(i, axis=axis)
        i = [6634, 6636, 6638, 6639, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6653, 6654, 6655, 6656, 6658, 6659, 6660, 6662, 6663, ...]
        values = undefined
        values.DataFrame.stack = undefined
        axis = 0
        axis.Return = undefined
        result = undefined
   1715                     copy=True
   1716                 else:
   1717                     new_values = self._data.fast_xs(i)
1718

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/generic.pyc in take(self=<class 'pandas.core.frame.DataFrame'> instance, indices=[6634, 6636, 6638, 6639, 6640, 6642, 6644, 6646, 6648, 6650, 6652, 6653, 6654, 6655, 6656, 6658, 6659, 6660, 6662, 6663, ...], axis=0, convert=True, is_copy=True)
   1346         taken : type of caller
   1347         """
1348
   1349         new_data = self._data.take(indices,
   1350                                    axis=self._get_block_manager_axis(axis),
-> 1351                                    convert=True, verify=True)
   1352         result = self._constructor(new_data).__finalize__(self)
1353
   1354         # maybe set copy if we didn't actually change the index
   1355         if is_copy:

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/internals.pyc in take(self=BlockManager
Items: Index([u'1516 Quinoa Weisse'...ock: slice(5239, 5240, 1), 1 x 20000, dtype: bool, indexer=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), axis=1, verify=True, convert=True)
   3264                 raise Exception('Indices must be nonzero and less than '
   3265                                 'the axis length')
3266
   3267         new_labels = self.axes[axis].take(indexer)
   3268         return self.reindex_indexer(new_axis=new_labels, indexer=indexer,
-> 3269                                     axis=axis, allow_dups=True)
3270
   3271     def merge(self, other, lsuffix='', rsuffix=''):
   3272         if not self._is_indexed_like(other):
   3273             raise AssertionError('Must have same axes to merge managers')

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/internals.pyc in reindex_indexer(self=BlockManager
Items: Index([u'1516 Quinoa Weisse'...ock: slice(5239, 5240, 1), 1 x 20000, dtype: bool, new_axis=Int64Index([3317, 3318, 3319, 3319, 3320, 3321, ...381, 3382, 3382, 3383, 3383, ...], dtype='int64'), indexer=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), axis=1, fill_value=None, allow_dups=True, copy=True)
   3151                 indexer, fill_tuple=(fill_value,))
   3152         else:
   3153             new_blocks = [blk.take_nd(indexer, axis=axis,
   3154                                       fill_tuple=(fill_value if fill_value is not None else
   3155                                                   blk.fill_value,))
-> 3156                           for blk in self.blocks]
3157
   3158         new_axes = list(self.axes)
   3159         new_axes[axis] = new_axis
   3160         return self.__class__(new_blocks, new_axes)

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/internals.pyc in take_nd(self=FloatBlock: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1...6, 97, 98, 99, ...], 5813 x 20000, dtype: float64, indexer=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), axis=1, new_mgr_locs=None, fill_tuple=(nan,))
    846             new_values = com.take_nd(self.get_values(), indexer, axis=axis,
    847                                      allow_fill=False)
    848         else:
    849             fill_value = fill_tuple[0]
    850             new_values = com.take_nd(self.get_values(), indexer, axis=axis,
--> 851                                      allow_fill=True, fill_value=fill_value)
852
    853         if new_mgr_locs is None:
    854             if axis == 0:
    855                 slc = lib.indexer_as_slice(indexer)

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/core/common.pyc in take_nd(arr=memmap([[ 0.        ,  0.        ,  0.        , ...  0.        ,
         0.        ,  0.        ]]), indexer=array([ 6634,  6636,  6638, ..., 19997, 19998, 19999]), axis=1, out=array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
    ...0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]]), fill_value=nan, mask_info=None, allow_fill=True)
818
    819     func = _get_take_nd_function(arr.ndim, arr.dtype, out.dtype,
    820                                  axis=axis, mask_info=mask_info)
821
    822     indexer = _ensure_int64(indexer)
--> 823     func(arr, indexer, out, fill_value)
824
    825     if flip_order:
    826         out = out.T
    827     return out

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/algos.so in pandas.algos.take_2d_axis1_float64_float64 (pandas/algos.c:95466)()
4000
4001
4002
4003
4004
-> 4005 
4006
4007
4008
4009

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/algos.so in View.MemoryView.memoryview_cwrapper (pandas/algos.c:175798)()
609
610
611
612
613
--> 614 
615
616
617
618

...........................................................................
/home/user/anaconda/lib/python2.7/site-packages/pandas/algos.so in View.MemoryView.memoryview.__cinit__ (pandas/algos.c:172387)()
316
317
318
319
320
--> 321 
322
323
324
325

ValueError: buffer source array is read-only
___________________________________________________________________________
```

pd.show_versions()

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Linux
OS-release: 3.16.0-34-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.16.0
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.2
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: 2.0.2
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.7.2
lxml: 3.4.2
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 0.9.9
pymysql: None
psycopg2: 2.6 (dt dec pq3 ext)
```
