How to create a Multi-index dataframe

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In summary, the conversation discusses the creation of a multi index dataframe in Python. The individual has attempted to do so using a specific approach, but it did not provide the desired output. They mention that Pandas is not designed for 3-D indexing and suggest using Numpy for such manipulations.
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I haven't gotten into the weeds of this in while, but I think what you're asking is simply not in Pandas. Pandas is designed, in effect, to be excel spreadsheets via python (with the added capabilities that come with it).

Spreadsheets are fundamentally indexed with (i,j) pairs. There is no third index. (You could try to synthetically creating such a thing via a mapping formula that you come up with though that sounds unpleasant).

If you want to use (i,j,k) indexing, this is 3-D tensor territory that is easy to manipulate via arrays in Numpy. It is not Pandas.
 
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FAQ: How to create a Multi-index dataframe

How do I create a multi-index dataframe in Python?

To create a multi-index dataframe in Python, you can use the pd.MultiIndex.from_arrays() function to specify the index labels and then pass it as an argument to the pd.DataFrame() function along with your data.

Can I have more than two levels in a multi-index dataframe?

Yes, you can have multiple levels in a multi-index dataframe by passing a list of arrays to the pd.MultiIndex.from_arrays() function.

How do I specify the column names in a multi-index dataframe?

To specify the column names in a multi-index dataframe, you can use the pd.MultiIndex.from_product() function to create a multi-index object with all possible combinations of the specified levels, and then pass it as an argument to the pd.DataFrame() function along with your data.

Can I create a multi-index dataframe from an existing dataframe?

Yes, you can create a multi-index dataframe from an existing dataframe by using the pd.DataFrame.set_index() function with the append=True parameter. This will add the specified columns as additional levels to the existing index.

How do I access data from a specific level in a multi-index dataframe?

To access data from a specific level in a multi-index dataframe, you can use the df.loc[] function and specify the level names or numbers in the index. You can also use the df.xs() function to extract data from a specific level without specifying the other levels in the index.

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