DataFrame.dtypes error when training model using xgboost I am getting a DataFrame.dtypes error while following the last steps of this tutorial.

Here is my code:

import xgboost as xgb
regr = xgb.XGBRegressor(colsample_bytree=0.2,
                       gamma=0.0,
                       learning_rate=0.05,
                       max_depth=6,
                       min_child_weight=1.5,
                       n_estimators=7200,
                       reg_alpha=0.9,
                       reg_lambda=0.6,
                       subsample=0.2,
                       seed=42,
                       silent=1)

regr.fit(train_new, label_df)


And this is the error I am receiving:

ValueErrorTraceback (most recent call last)
&lt;ipython-input-64-010296d611e9&gt; in &lt;module&gt;()
     12                        silent=1)
     13 
---&gt; 14 regr.fit(train_new, label_df)

D:\anacodna\lib\site-packages\xgboost\sklearn.pyc in fit(self, X, y, sample_weight, eval_set, eval_metric, early_stopping_rounds, verbose, xgb_model, sample_weight_eval_set, callbacks)
    358                                    missing=self.missing, nthread=self.n_jobs)
    359         else:
--&gt; 360             trainDmatrix = DMatrix(X, label=y, missing=self.missing, nthread=self.n_jobs)
    361 
    362         evals_result = {}

D:\anacodna\lib\site-packages\xgboost\core.pyc in __init__(self, data, label, missing, weight, silent, feature_names, feature_types, nthread)
    378         data, feature_names, feature_types = _maybe_pandas_data(data,
    379                                                                 feature_names,
--&gt; 380                                                                 feature_types)
    381 
    382         data, feature_names, feature_types = _maybe_dt_data(data,

D:\anacodna\lib\site-packages\xgboost\core.pyc in _maybe_pandas_data(data, feature_names, feature_types)
    237         msg = """DataFrame.dtypes for data must be int, float or bool.
    238                 Did not expect the data types in fields """
--&gt; 239         raise ValueError(msg + ', '.join(bad_fields))
    240 
    241     if feature_names is None:

ValueError: DataFrame.dtypes for data must be int, float or bool.
                Did not expect the data types in fields Alley, Condition2, Electrical, GarageType, GarageYrBlt, Heating, LandContour, LandSlope, LotShape, MiscFeature, PavedDrive, RoofMatl, Street, Utilities
Check the values of train_new. You'll see that the columns mentionned are not of the expected types. 

Another suggestion, i'm not sure of xgboost's handling of nulls. Might be that in those columns aswell.