Pandas gives 600 line long ValueError while runing sklearn GridSearchCV

[ek-ok]

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)

[shoyer]

A few thoughts. First, this is just as much if not more a scikit learn issue than a pandas issue -- last time I checked they didn't support dataframes as native input. Second, as a work around, try passing X.values and y.values -- that would help identify if this is really something related to pandas or not. If it does seem to be an issue that only appears when both pandas and scikit learn are combined, it would help if you could provide a full example that reproduces it, including input data.

[ek-ok]

As you suggested, X.values and y.values seem to be solving this issue. Thanks for your quick response and support!

[amueller]

@shoyer I agree this is a sklearn issue. We should support pd dataframes as of 0.16. I'll check where we messed up.

[ek-ok]

@amueller thank you