@@ -45,14 +45,8 @@ def test_columntransformer_standalone_fit_and_transform(
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)
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result = transformer .transform (new_penguins_df ).to_pandas ()
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- # TODO: bug? feature columns seem to be in nondeterministic random order
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- # workaround: sort columns by name. Can't repro it in pantheon, so could
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- # be a bigframes issue...
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- result = result .reindex (sorted (result .columns ), axis = 1 )
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-
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expected = pandas .DataFrame (
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{
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- "min_max_scaled_culmen_length_mm" : [0.269 , 0.232 , 0.210 ],
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"onehotencoded_species" : [
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[{"index" : 1 , "value" : 1.0 }],
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[{"index" : 1 , "value" : 1.0 }],
@@ -63,6 +57,7 @@ def test_columntransformer_standalone_fit_and_transform(
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- 0.9945520581113803 ,
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- 1.104611490204711 ,
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],
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+ "min_max_scaled_culmen_length_mm" : [0.269 , 0.232 , 0.210 ],
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"standard_scaled_flipper_length_mm" : [- 0.350044 , - 1.418336 , - 0.9198 ],
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},
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index = pandas .Index ([1633 , 1672 , 1690 ], dtype = "Int64" , name = "tag_number" ),
@@ -91,11 +86,6 @@ def test_columntransformer_standalone_fit_transform(new_penguins_df):
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new_penguins_df [["species" , "culmen_length_mm" , "flipper_length_mm" ]]
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).to_pandas ()
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- # TODO: bug? feature columns seem to be in nondeterministic random order
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- # workaround: sort columns by name. Can't repro it in pantheon, so could
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- # be a bigframes issue...
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- result = result .reindex (sorted (result .columns ), axis = 1 )
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-
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expected = pandas .DataFrame (
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{
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"onehotencoded_species" : [
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