Creating a dataframe with multi-index columns from a dictionary

Question

Suppose I have the following:

a data frame with multi-index columns

a dictionary that's been created from the data frame with multi-index columns in order to efficiently manipulate it.

df = pd.DataFrame([
         [100,90,80,70,36,45], 
         [101,78,65,88,55,78], 
         [92,77,42,79,43,32], 
         [103,98,76,54,45,65]], 
         index = pd.date_range(start='2022-01-01', periods=4)
)

df.columns = pd.MultiIndex.from_tuples(
        (("mkf", "Open"), 
         ("mkf", "Close"), 
         ("tdf", "Open"), 
         ("tdf","Close"), 
         ("ghi","Open"), 
         ("ghi", "Close"))
)
df
            mkf        tdf        ghi
           Open Close Open Close Open Close
2022-01-01  100    90   80    70   36    45
2022-01-02  101    78   65    88   55    78
2022-01-03   92    77   42    79   43    32
2022-01-04  103    98   76    54   45    65

df_dict = {c:df[c].assign(r=np.log(df[(c, 'Close')]).diff()) for c in df.columns.levels[0]}

df_dict
{'ghi':             Open  Close         r
 2022-01-01    36     45       NaN
 2022-01-02    55     78  0.550046
 2022-01-03    43     32 -0.890973
 2022-01-04    45     65  0.708651,
 'mkf':             Open  Close         r
 2022-01-01   100     90       NaN
 2022-01-02   101     78 -0.143101
 2022-01-03    92     77 -0.012903
 2022-01-04   103     98  0.241162,
 'tdf':             Open  Close         r
 2022-01-01    80     70       NaN
 2022-01-02    65     88  0.228842
 2022-01-03    42     79 -0.107889
 2022-01-04    76     54 -0.380464}

What is the best way to transform the dictionary back to a data frame in its original form (i.e. with multi-index columns)?

            mkf               tdf              ghi
           Open Close  r     Open Close  r    Open Close r
2022-01-01  100    90  NaN    80    70   NaN   36    45  NaN
2022-01-02  101    78  0.55   65    88  -0.14  55    78  0.23
2022-01-03   92    77 -0.89   42    79  -0.12  43    32 -0.10
2022-01-04  103    98  0.71   76    54   0.24  45    65 -0.38

user_14193915 · Answer

    pd.concat([df_dict[c] for c in df_dict.keys()], axis = 1, 
keys = df_dict.keys()) 

            ghi                  mkf                  tdf
           Open Close         r Open Close         r Open Close         r
2022-01-01   36    45       NaN  100    90       NaN   80    70       NaN
2022-01-02   55    78  0.550046  101    78 -0.143101   65    88  0.228842
2022-01-03   43    32 -0.890973   92    77 -0.012903   42    79 -0.107889
2022-01-04   45    65  0.708651  103    98  0.241162   76    54 -0.380464

Creating a dataframe with multi-index columns from a dictionary

1 Answers