9ac163d0bb
* Allow import via python datatable. * Write unit tests * Refactor dt API functions * Refactor python code * Lint fixes * Address review comments
48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
# -*- coding: utf-8 -*-
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import unittest
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import testing as tm
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import xgboost as xgb
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try:
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import datatable as dt
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import pandas as pd
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except ImportError:
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pass
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tm._skip_if_no_dt()
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tm._skip_if_no_pandas()
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class TestDataTable(unittest.TestCase):
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def test_dt(self):
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df = pd.DataFrame([[1, 2., True], [2, 3., False]], columns=['a', 'b', 'c'])
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dtable = dt.Frame(df)
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labels = dt.Frame([1, 2])
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dm = xgb.DMatrix(dtable, label=labels)
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assert dm.feature_names == ['a', 'b', 'c']
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assert dm.feature_types == ['int', 'float', 'i']
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assert dm.num_row() == 2
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assert dm.num_col() == 3
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# overwrite feature_names
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dm = xgb.DMatrix(dtable, label=pd.Series([1, 2]),
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feature_names=['x', 'y', 'z'])
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assert dm.feature_names == ['x', 'y', 'z']
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assert dm.num_row() == 2
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assert dm.num_col() == 3
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# incorrect dtypes
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df = pd.DataFrame([[1, 2., 'x'], [2, 3., 'y']], columns=['a', 'b', 'c'])
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dtable = dt.Frame(df)
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self.assertRaises(ValueError, xgb.DMatrix, dtable)
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df = pd.DataFrame({'A=1': [1, 2, 3], 'A=2': [4, 5, 6]})
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dtable = dt.Frame(df)
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dm = xgb.DMatrix(dtable)
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assert dm.feature_names == ['A=1', 'A=2']
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assert dm.feature_types == ['int', 'int']
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assert dm.num_row() == 3
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assert dm.num_col() == 2
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