diff --git a/python-package/xgboost/core.py b/python-package/xgboost/core.py index 055f7ebca..489c4a9b5 100644 --- a/python-package/xgboost/core.py +++ b/python-package/xgboost/core.py @@ -138,27 +138,42 @@ def c_array(ctype, values): return (ctype * len(values))(*values) -def _maybe_from_pandas(data, feature_names, feature_types): +def _maybe_from_pandas(data, label, feature_names, feature_types): """ Extract internal data from pd.DataFrame """ try: import pandas as pd except ImportError: - return data, feature_names, feature_types + return data, label, feature_names, feature_types if not isinstance(data, pd.DataFrame): - return data, feature_names, feature_types + return data, label, feature_names, feature_types - dtypes = data.dtypes - if not all(dtype.name in ('int64', 'float64', 'bool') for dtype in dtypes): - raise ValueError('DataFrame.dtypes must be int, float or bool') + mapper = {'int8': 'int', 'int16': 'int', 'int32': 'int', 'int64': 'int', + 'uint8': 'int', 'uint16': 'int', 'uint32': 'int', 'uint64': 'int', + 'float16': 'float', 'float32': 'float', 'float64': 'float', + 'bool': 'i'} + + data_dtypes = data.dtypes + if not all(dtype.name in (mapper.keys()) for dtype in data_dtypes): + raise ValueError('DataFrame.dtypes for data must be int, float or bool') + + if label is not None: + if isinstance(label, pd.DataFrame): + label_dtypes = label.dtypes + if not all(dtype.name in (mapper.keys()) for dtype in label_dtypes): + raise ValueError('DataFrame.dtypes for label must be int, float or bool') + else: + label = label.values.astype('float') if feature_names is None: feature_names = data.columns.format() + if feature_types is None: - mapper = {'int64': 'int', 'float64': 'q', 'bool': 'i'} - feature_types = [mapper[dtype.name] for dtype in dtypes] + feature_types = [mapper[dtype.name] for dtype in data_dtypes] + data = data.values.astype('float') - return data, feature_names, feature_types + + return data, label, feature_names, feature_types class DMatrix(object): """Data Matrix used in XGBoost. @@ -192,9 +207,9 @@ class DMatrix(object): silent : boolean, optional Whether print messages during construction feature_names : list, optional - Labels for features. + Set names for features. feature_types : list, optional - Labels for features. + Set types for features. """ # force into void_p, mac need to pass things in as void_p if data is None: @@ -204,8 +219,10 @@ class DMatrix(object): klass = getattr(getattr(data, '__class__', None), '__name__', None) if klass == 'DataFrame': # once check class name to avoid unnecessary pandas import - data, feature_names, feature_types = _maybe_from_pandas(data, feature_names, - feature_types) + data, label, feature_names, feature_types = _maybe_from_pandas(data, + label, + feature_names, + feature_types) if isinstance(data, STRING_TYPES): self.handle = ctypes.c_void_p() @@ -520,10 +537,10 @@ class DMatrix(object): if len(feature_names) != self.num_col(): msg = 'feature_names must have the same length as data' raise ValueError(msg) - # prohibit to use symbols may affect to parse. e.g. ``[]=.`` - if not all(isinstance(f, STRING_TYPES) and f.isalnum() + # prohibit to use symbols may affect to parse. e.g. []< + if not all(isinstance(f, STRING_TYPES) and not any(x in f for x in {'[', ']', '<'}) for f in feature_names): - raise ValueError('all feature_names must be alphanumerics') + raise ValueError('feature_names may not contain [, ] or <') else: # reset feature_types also self.feature_types = None @@ -556,12 +573,11 @@ class DMatrix(object): if len(feature_types) != self.num_col(): msg = 'feature_types must have the same length as data' raise ValueError(msg) - # prohibit to use symbols may affect to parse. e.g. ``[]=.`` - valid = ('q', 'i', 'int', 'float') + valid = ('int', 'float', 'i', 'q') if not all(isinstance(f, STRING_TYPES) and f in valid for f in feature_types): - raise ValueError('all feature_names must be {i, q, int, float}') + raise ValueError('All feature_names must be {int, float, i, q}') self._feature_types = feature_types diff --git a/tests/python/test_basic.py b/tests/python/test_basic.py index a8e0d5238..db112372f 100644 --- a/tests/python/test_basic.py +++ b/tests/python/test_basic.py @@ -48,7 +48,7 @@ class TestBasic(unittest.TestCase): feature_names=['a', 'b', 'c', 'd', 'd']) # contains symbol self.assertRaises(ValueError, xgb.DMatrix, data, - feature_names=['a', 'b', 'c', 'd', 'e=1']) + feature_names=['a', 'b', 'c', 'd', 'e<1']) dm = xgb.DMatrix(data) dm.feature_names = list('abcde') @@ -105,7 +105,7 @@ class TestBasic(unittest.TestCase): df = pd.DataFrame([[1, 2., True], [2, 3., False]], columns=['a', 'b', 'c']) dm = xgb.DMatrix(df, label=pd.Series([1, 2])) assert dm.feature_names == ['a', 'b', 'c'] - assert dm.feature_types == ['int', 'q', 'i'] + assert dm.feature_types == ['int', 'float', 'i'] assert dm.num_row() == 2 assert dm.num_col() == 3 @@ -125,14 +125,14 @@ class TestBasic(unittest.TestCase): df = pd.DataFrame([[1, 2., True], [2, 3., False]]) dm = xgb.DMatrix(df, label=pd.Series([1, 2])) assert dm.feature_names == ['0', '1', '2'] - assert dm.feature_types == ['int', 'q', 'i'] + assert dm.feature_types == ['int', 'float', 'i'] assert dm.num_row() == 2 assert dm.num_col() == 3 df = pd.DataFrame([[1, 2., 1], [2, 3., 1]], columns=[4, 5, 6]) dm = xgb.DMatrix(df, label=pd.Series([1, 2])) assert dm.feature_names == ['4', '5', '6'] - assert dm.feature_types == ['int', 'q', 'int'] + assert dm.feature_types == ['int', 'float', 'int'] assert dm.num_row() == 2 assert dm.num_col() == 3 @@ -293,4 +293,4 @@ class TestBasic(unittest.TestCase): assert isinstance(g, Digraph) ax = xgb.plot_tree(classifier, num_trees=0) - assert isinstance(ax, Axes) \ No newline at end of file + assert isinstance(ax, Axes)