Should a data analyst write their own code if they cannot finish their own analysis?

So the situation is as follows:

A data analyst is busy with an analysis using Excel. It turns out that they cannot validate intermediate results as that would require either advanced knowledge of Excel or basic python scripting knowledge. Both of those knowledge "upgrades" are apparently not viable/desirable options for the analyst.

To help this situation, the Data Science team created a few scripts and a streamlit app that the data analyst can run on their own. Also, the analyst got a clear explanation of which code lines to modify to in case he wants to change their model, as that it is like 10 lines of code in pandas itself. The data analyst has basic coding knowledge of Java and C++ and an engineering master's degree. They know for loops, conditional, variable assignment, function definition and all the programming basics.

During the explanation they could already spots some bugs in the code right away. Nonetheless, the analyst keeps asking for data scientists to write code as that would be 'too time consuming' for their time while it is just a small 'change' to do for a data scientist.

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What do you think? What are the boundaries of a data analyst role in this case? Is it fair to ask they can run some python code on their own? Or is basic Excel all they need to know for their job?