Element named "None" gets interpreted as 'nan' when using "execute_mdx_dataframe(..., use_blob=True)"

[bdunleavy22]

Describe the bug
When an execute_mdx_dataframe is run with use_blob=True, any element named "None" will be interpreted as NaN, instead of a string "None".
This behavior is a result of lines 551/556 in 'build_dataframe_from_csv' in "Utils.py", df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=["", None], keep_default_na=False, **kwargs). If that line is changed to df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=[""], keep_default_na=False, **kwargs) (removing None from na_values), the function then behaves as expected.
I don't know why, but it seems like pandas is treating None as "None"?

To Reproduce

1. Have a cube where a dimension has an element named "None".
2. Run the function execute_mdx_dataframe, with use_blob=True and the "None" element is included in the MDXView
3. The element will be returned as NaN in the DataFrame.
4. (This might also be true for cell values that are "None", I have not tested that)

Expected behavior
Elements named "None" would be in the DataFrame as "None" instead of "NaN".

Version
TM1py 2.0.4
TM1 Server Version: 11.8.02500.3

[MariusWirtz]

Good catch. Thank you for raising this, @bennybooo22.

We must not substitute None element names with nan in element columns.
I will look into this