Add SDMX analysis notebooks

[rohitkumarbhagat]

Adds three Colab tutorials using Data Commons SDMX APIs to analyze census data, income
distribution, and obesity prevalence. The notebooks use SDMX for statistical observations and
the Python client for place names.

Copied from prototypes, with Colab links updated to api-python and links added to the
notebooks README.

Validation: Notebook schema, code syntax, and diff checks passed.

[gemini-code-assist]

Code Review

This pull request introduces three new Jupyter notebooks demonstrating the integration of the Data Commons Python client with SDMX APIs to analyze census data, household income distribution, and obesity prevalence, along with an updated README. Feedback on these additions highlights a data loss issue in the census notebook where pivoting on non-unique place names collapses duplicate geographic entities, and raises security concerns regarding the hardcoded Google API keys present across all three notebooks.

[rohitkumarbhagat]

/gemini review

[gemini-code-assist]

Code Review

This pull request adds three new Colab notebooks demonstrating how to use the Data Commons Python client and SDMX APIs to analyze census data, income distribution, and obesity prevalence, along with updating the directory's README. The review feedback highlights a critical bug in the census notebook where setting frame.index.name = None on a MultiIndex will raise an AttributeError, suggesting frame.index.names = [None, None] instead. Additionally, it is recommended to improve the API key validation across all three notebooks to explicitly check for the default placeholder string and provide a more helpful error message.

[kmoscoe]

Should we perhaps create an sdmx subdirectory under notebooks and put all these in there. It might be more obvious than just the suffixes on the file.