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  1. list of dataframes (ex. dfs = [df1, df2, ...])

  2. all dataframe columns is multiindex (ex. [("something", "id",), ("something", "age"), ...]) enter image description here

  3. i want to set "concept_id" to Key and create a new dataframe like this: enter image description here

i try using python pandas, but it was hard. (multiindex is really hard) what should i do?

  1. pd.concat(dfs, keys=["concept_id"], join="outer", axis=1)

It didn't come close to the correct answer.

  1. reduce(lambda df1, df2: pd.merge(df1, df2, on="concept_id", how="outer"), dfs)

raised error : xlsxwriter.exceptions.OverlappingRange: Merge range 'B1:J1' overlaps previous merge range 'B1:J1'.

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IIUC, you need to set all "something" columns as index during the concat (if you want a unique set of those 3 columns, one can assume that they are all common), then post-process the output to reorganize the levels (e.g. with reorder_levels):

idx = pd.MultiIndex.from_tuples([('something', 'id'), ('something', 'age'), ('something', 'label_en'),
                                 ('2023', '01'), ('2023', '02')])
df1 = pd.DataFrame(1, columns=idx, index=[0])
df2 = pd.DataFrame(1, columns=idx, index=[0])

dfs = [df1, df2]

cols = [('something', 'id'), ('something', 'age'), ('something', 'label_en')]

out = (pd.concat([d.set_index(cols) for d in dfs],
                 keys=['df1', 'df2'], join='outer', axis=1)
         .reorder_levels([1,2,0], axis=1)
         .reset_index()
         .reorder_levels([2,0,1], axis=1)
      )

Output:

                          df1     df2   
  something              2023    2023   
         id age label_en   01 02   01 02
0         1   1        1    1  1    1  1
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