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Allow dtype to be inferred by pandas with argument infer_dtype in execute_mdx_dataframe_shaped #879

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merged 1 commit into from
Mar 27, 2023
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Allow dtype to be inferred by pandas with argument infer_dtype in execute_mdx_dataframe_shaped #879

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9 changes: 7 additions & 2 deletions TM1py/Services/CellService.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2798,13 +2798,15 @@ def extract_cellset_dataframe(
@tidy_cellset
@require_pandas
def extract_cellset_dataframe_shaped(self, cellset_id: str, sandbox_name: str = None,
display_attribute: bool = False, **kwargs) -> 'pd.DataFrame':
display_attribute: bool = False, infer_dtype: bool = False, **kwargs) -> 'pd.DataFrame':
""" Retrieves data from cellset in the shape of the query.
Dimensions on rows can be stacked. One dimension must be placed on columns. Title selections are ignored.

:param cellset_id
:param sandbox_name: str
:param display_attribute: bool, show element name or first attribute from MDX PROPERTIES clause
:param infer_dtype: bool, if True, lets pandas infer dtypes, otherwise all columns will be of type str.

"""
url = "/api/v1/Cellsets('{}')?$expand=" \
"Axes($filter=Ordinal eq 0 or Ordinal eq 1;$expand=Tuples(" \
Expand Down Expand Up @@ -2860,7 +2862,10 @@ def extract_cellset_dataframe_shaped(self, cellset_id: str, sandbox_name: str =

for element_tuple, cells in zip(element_names_by_row, cell_values_by_row):
body.append(list(element_tuple) + cells)
return pd.DataFrame(body, columns=headers, dtype=str)
if infer_dtype:
return pd.DataFrame(body, columns=headers)
else:
return pd.DataFrame(body, columns=headers, dtype=str)

@require_pandas
def extract_cellset_dataframe_pivot(self, cellset_id: str, dropna: bool = False, fill_value: bool = False,
Expand Down