8000 Re-implement df.pct_change based on new structure by densmirn · Pull Request #847 · IntelPython/sdc · GitHub
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Re-implement df.pct_change based on new structure #847

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May 20, 2020
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Re-implement df.pct_change based on new structure #847

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10 changes: 6 additions & 4 deletions sdc/datatypes/hpat_pandas_dataframe_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -640,13 +640,15 @@ def copy_overload(df, deep=True):
return sdc_pandas_dataframe_copy_codegen(df, params, series_params)


def _dataframe_apply_columns_codegen(func_name, func_params, series_params, columns):
def _dataframe_apply_columns_codegen(func_name, func_params, series_params, columns, column_loc):
result_name = []
joined = ', '.join(func_params)
func_lines = [f'def _df_{func_name}_impl({joined}):']
for i, c in enumerate(columns):
col_loc = column_loc[c]
type_id, col_id = col_loc.type_id, col_loc.col_id
result_c = f'result_{i}'
func_lines += [f' series_{i} = pandas.Series({func_params[0]}._data[{i}])',
func_lines += [f' series_{i} = pandas.Series({func_params[0]}._data[{type_id}][{col_id}])',
f' {result_c} = series_{i}.{func_name}({series_params})']
result_name.append((result_c, c))

Expand All @@ -673,8 +675,8 @@ def sdc_pandas_dataframe_apply_columns(df, func_name, params, ser_params):

df_func_name = f'_df_{func_name}_impl'

func_text, global_vars = _dataframe_apply_columns_codegen(func_name, all_params, s_par, df.columns)

func_text, global_vars = _dataframe_apply_columns_codegen(func_name, all_params, s_par,
df.columns, df.column_loc)
loc_vars = {}
exec(func_text, global_vars, loc_vars)
_reduce_impl = loc_vars[df_func_name]
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2 changes: 1 addition & 1 deletion sdc/tests/test_dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1347,7 +1347,7 @@ def test_impl(df, deep):
with self.subTest(index=idx, deep=deep):
pd.testing.assert_frame_equal(sdc_func(df, deep), test_impl(df, deep))

@dfRefactoringNotImplemented
@dfRefactoringNotImplemented # required re-implementing DataFrame boxing
def test_pct_change1(self):
def test_impl(n):
df = pd.DataFrame({'A': np.arange(n) + 1.0, 'B': np.arange(n) + 1})
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