Where are the docs for idiots like me?

[hunterhogan]

c:\apps\mapFolding\mapFolding\algorithms\mmPandas.py:48: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

  dataframeCurveLocations['analyzed'] = 0

Ok, df.loc[row_indexer, "col"] = values. I can do that. I don't have a row indexer, so it's easy: dataframeCurveLocations.loc['analyzed'] = 0.

...
TypeError: Cannot perform 'and_' with a dtyped [float64] array and scalar of type [bool]

I don't have float or scalar bool in the module, so I got the wrong cow.

I'll read the documentation in the error message.

Compare these two access methods:

dfmi['one']['second']
Out[384]: 
0    b
1    f
2    j
3    n
Name: second, dtype: object

dfmi.loc[:, ('one', 'second')]
Out[385]: 
0    b
1    f
2    j
3    n
Name: (one, second), dtype: object 

I don't know what to compare between the two. They look the same to me.

These both yield the same results...

So they are the same?

Why does assignment fail when using chained indexing?

I don't even know what chained indexing means. I thought the topic was "Returning a view versus a copy." In dataframeCurveLocations['analyzed'] = 0, how does 0 have a view or a copy?

Nah, man. If I were in the mood to be abused and told that if I really needed help, I would have done things the right way, I would call one of my parents: I don't need StackOverflow for that.

So, where are the stupid-people docs? After three days of trying, I don't understand. Copilot in VS Code doesn't understand: Claude Sonnet 4, GPT-5 (Preview), MCP context7, weblinks to pandas.pydata.org. I don't get it.

I don't want help fixing this warning. I have tons of problems, so I need the dumbed-down docs.

[mroeschke]

Sorry you're having trouble interpreting the docs, but this a broad ask which doesn't really have a solution from the maintainers. May I suggest searching for other developer blogs or videos online describing pandas indexing (which understandably a complicated, but powerful, selection API)

I don't know what to compare between the two. They look the same to me.

The difference is in the number of operations, dfmi['one']['second'] requires 2 indexing operations (i.e. 2 "chained indexing" operations) and dfmi.loc[:, ('one', 'second')] requires 1 indexing operations.

So they are the same?

Both methods may return the same result, but, due to implementation details, the indexed result might share same data as the original DataFrame. FWIW this all will be simplified once pandas 3.0 comes out.