I have a dataframe with multiple levels, eg:
idx = pd.MultiIndex.from_product((['foo', 'bar'], ['one', 'five', 'three' 'four']),
names=['first', 'second'])
df = pd.DataFrame({'A': [np.nan, 12, np.nan, 11, 16, 12, 11, np.nan]}, index=idx).dropna().astype(int)
A
first second
foo five 12
four 11
bar one 16
five 12
three 11
I want to create a new column using the index level titled second
, so that I get
A B
first second
foo five 12 five
four 11 four
bar one 16 one
five 12 five
three 11 three
I can do this by resetting the index, copying the column, then re-applying, but that seems more round-about.
I tried df.index.levels[1]
, but that creates a sorted list, it doesn't preserve the order.
If it was a single index, I would use df.index
but in a multiindex that creates a column of tuples.
If this is resolved elsewhere, please share as I haven't had any luck searching the stackoverflow archives.
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