@@ -2856,9 +2856,14 @@ def test_pivot_margins_with_none_index(self):
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def test_pivot_with_pyarrow_categorical (self ):
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# GH#53051
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- # Create dataframe with categorical colum
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+ pytest .importorskip ("pyarrow" )
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+
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+ # Create dataframe with categorical column
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df = (
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- pd .DataFrame ([("A" , 1 ), ("B" , 2 ), ("C" , 3 )], columns = ["string_column" , "number_column" ])
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+ DataFrame (
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+ [("A" , 1 ), ("B" , 2 ), ("C" , 3 )],
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+ columns = ["string_column" , "number_column" ],
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+ )
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.astype ({"string_column" : "string" , "number_column" : "float32" })
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.astype ({"string_column" : "category" , "number_column" : "float32" })
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)
@@ -2869,25 +2874,18 @@ def test_pivot_with_pyarrow_categorical(self):
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buffer .seek (0 ) # Reset buffer position
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df = pd .read_parquet (buffer , dtype_backend = "pyarrow" )
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-
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# Check that pivot works
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df = df .pivot (columns = ["string_column" ], values = ["number_column" ])
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# Assert that values of result are correct to prevent silent failure
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- multi_index = pd .MultiIndex .from_arrays (
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- [
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- ["number_column" , "number_column" , "number_column" ],
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- ["A" , "B" , "C" ]
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- ],
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- names = (None , "string_column" )
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+ multi_index = MultiIndex .from_arrays (
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+ [["number_column" , "number_column" , "number_column" ], ["A" , "B" , "C" ]],
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+ names = (None , "string_column" ),
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)
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- df_expected = pd .DataFrame (
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- [
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- [1.0 , np .nan , np .nan ],
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- [np .nan , 2.0 , np .nan ],
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- [np .nan , np .nan , 3.0 ]
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- ],
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- columns = multi_index
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+ df_expected = DataFrame (
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+ [[1.0 , np .nan , np .nan ], [np .nan , 2.0 , np .nan ], [np .nan , np .nan , 3.0 ]],
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+ columns = multi_index ,
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+ )
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+ tm .assert_frame_equal (
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+ df , df_expected , check_dtype = False , check_column_type = False
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)
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- tm .assert_frame_equal (df , df_expected , check_dtype = False , check_column_type = False )
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-
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