h2o_output_pandas.txt

# groupby-pandas.py
loading dataset G1_1e7_1e2_0_0
10000000
grouping...
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: float64
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dtype: float64
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r2    0.000125
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r2    0.0005
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r2    0.00002
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dtype: float64
r2    0.000032
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r2    0.002075
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dtype: float64
r2    0.000014
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r2    0.000216
dtype: float64
r2    0.000008
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r2    0.000014
dtype: float64
(10000, 4)
# sm03,,1601065110.7760277,groupby,G1_1e7_1e2_0_0,10000000,regression v1 v2 by id2 id4,10000,4,pandas,1.1.2,2a7d3326dee660824a8433ffd01065f8ac37f7d6,.groupby,1,14.298,1.015,TRUE,9.894,0.0,,FALSE
(10000, 4)
# sm03,,1601065120.9938655,groupby,G1_1e7_1e2_0_0,10000000,regression v1 v2 by id2 id4,10000,4,pandas,1.1.2,2a7d3326dee660824a8433ffd01065f8ac37f7d6,.groupby,2,10.166,1.015,TRUE,9.894,0.0,,FALSE
   index    id2  id4        r2
0      0  id001    1  0.001056
1      1  id001    2  0.000755
2      2  id001    3  0.000443
      index    id2  id4        r2
9997   9997  id100   98  0.000236
9998   9998  id100   99  0.003032
9999   9999  id100  100  0.000014