builtins.ValueError

ValueError: Found array with 0 sample(s) (shape=(0, 4)) while a minimum of 1 is required.

Traceback (most recent call last)

File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 2309, in __call__


    def __call__(self, environ, start_response):
        """The WSGI server calls the Flask application object as the
        WSGI application. This calls :meth:`wsgi_app` which can be
        wrapped to applying middleware."""
        return self.wsgi_app(environ, start_response)

    def __repr__(self):
        return '<%s %r>' % (
            self.__class__.__name__,
            self.name,
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 2295, in wsgi_app

            try:
                ctx.push()
                response = self.full_dispatch_request()
            except Exception as e:
                error = e
                response = self.handle_exception(e)
            except:
                error = sys.exc_info()[1]
                raise
            return response(environ, start_response)
        finally:
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 1741, in handle_exception

            # if we want to repropagate the exception, we can attempt to
            # raise it with the whole traceback in case we can do that
            # (the function was actually called from the except part)
            # otherwise, we just raise the error again
            if exc_value is e:
                reraise(exc_type, exc_value, tb)
            else:
                raise e

        self.log_exception((exc_type, exc_value, tb))
        if handler is None:
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\_compat.py", line 35, in reraise

    from io import StringIO

    def reraise(tp, value, tb=None):
        if value.__traceback__ is not tb:
            raise value.with_traceback(tb)
        raise value

    implements_to_string = _identity

else:
    text_type = unicode
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 2292, in wsgi_app

        ctx = self.request_context(environ)
        error = None
        try:
            try:
                ctx.push()
                response = self.full_dispatch_request()
            except Exception as e:
                error = e
                response = self.handle_exception(e)
            except:
                error = sys.exc_info()[1]
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 1815, in full_dispatch_request

            request_started.send(self)
            rv = self.preprocess_request()
            if rv is None:
                rv = self.dispatch_request()
        except Exception as e:
            rv = self.handle_user_exception(e)
        return self.finalize_request(rv)

    def finalize_request(self, rv, from_error_handler=False):
        """Given the return value from a view function this finalizes
        the request by converting it into a response and invoking the
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 1718, in handle_user_exception

            return self.handle_http_exception(e)

        handler = self._find_error_handler(e)

        if handler is None:
            reraise(exc_type, exc_value, tb)
        return handler(e)

    def handle_exception(self, e):
        """Default exception handling that kicks in when an exception
        occurs that is not caught.  In debug mode the exception will
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\_compat.py", line 35, in reraise

    from io import StringIO

    def reraise(tp, value, tb=None):
        if value.__traceback__ is not tb:
            raise value.with_traceback(tb)
        raise value

    implements_to_string = _identity

else:
    text_type = unicode
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 1813, in full_dispatch_request

        self.try_trigger_before_first_request_functions()
        try:
            request_started.send(self)
            rv = self.preprocess_request()
            if rv is None:
                rv = self.dispatch_request()
        except Exception as e:
            rv = self.handle_user_exception(e)
        return self.finalize_request(rv)

    def finalize_request(self, rv, from_error_handler=False):
File "C:\ProgramData\Anaconda3\lib\site-packages\flask\app.py", line 1799, in dispatch_request

        # request came with the OPTIONS method, reply automatically
        if getattr(rule, 'provide_automatic_options', False) \
           and req.method == 'OPTIONS':
            return self.make_default_options_response()
        # otherwise dispatch to the handler for that endpoint
        return self.view_functions[rule.endpoint](**req.view_args)

    def full_dispatch_request(self):
        """Dispatches the request and on top of that performs request
        pre and postprocessing as well as HTTP exception catching and
        error handling.
File "C:\Users\Tomasz\Desktop\CreditMe\AssessingService.py", line 14, in predict

def predict():
    json_ = request.json
    query = pd.DataFrame(json_)
    query = query.reindex(columns=model_columns)
    print(query)
    prediction = list(lr.predict(query))
    return jsonify({'prediction': str(prediction)})

port=33333
lr = joblib.load("PickledModel.pkl")
model_columns = joblib.load("PickledModelColumns.pkl")
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\linear_model\base.py", line 281, in predict

        Returns
        -------
        C : array, shape [n_samples]
            Predicted class label per sample.
        """
        scores = self.decision_function(X)
        if len(scores.shape) == 1:
            indices = (scores > 0).astype(np.int)
        else:
            indices = scores.argmax(axis=1)
        return self.classes_[indices]
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\linear_model\base.py", line 257, in decision_function

        """
        if not hasattr(self, 'coef_') or self.coef_ is None:
            raise NotFittedError("This %(name)s instance is not fitted "
                                 "yet" % {'name': type(self).__name__})

        X = check_array(X, accept_sparse='csr')

        n_features = self.coef_.shape[1]
        if X.shape[1] != n_features:
            raise ValueError("X has %d features per sample; expecting %d"
                             % (X.shape[1], n_features))
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 582, in check_array

        n_samples = _num_samples(array)
        if n_samples < ensure_min_samples:
            raise ValueError("Found array with %d sample(s) (shape=%s) while a"
                             " minimum of %d is required%s."
                             % (n_samples, shape_repr, ensure_min_samples,
                                context))

    if ensure_min_features > 0 and array.ndim == 2:
        n_features = array.shape[1]
        if n_features < ensure_min_features:
            raise ValueError("Found array with %d feature(s) (shape=%s) while"
ValueError: Found array with 0 sample(s) (shape=(0, 4)) while a minimum of 1 is required.