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问题:
I would like to add a column to the second level of a multiindex column dataframe.
In [151]: df Out[151]: first bar baz second one two one two A 0.487880 -0.487661 -1.030176 0.100813 B 0.267913 1.918923 0.132791 0.178503 C 1.550526 -0.312235 -1.177689 -0.081596
The usual trick of direct assignment does not work:
In [152]: df['bar']['three'] = [0, 1, 2] In [153]: df Out[153]: first bar baz second one two one two A 0.487880 -0.487661 -1.030176 0.100813 B 0.267913 1.918923 0.132791 0.178503 C 1.550526 -0.312235 -1.177689 -0.081596
How can I add the third row to under "bar"?
回答1:
It's actually pretty simple (FWIW, I originally thought to do it your way):
df['bar', 'three'] = [0, 1, 2] df = df.sort_index(axis=1) print(df) bar baz one two three one two A -0.212901 0.503615 0 -1.660945 0.446778 B -0.803926 -0.417570 1 -0.336827 0.989343 C 3.400885 -0.214245 2 0.895745 1.011671
回答2:
If we want to add a multi-level column:
Source DF:
In [221]: df Out[221]: first bar baz second one two one two A -1.089798 2.053026 0.470218 1.440740 B 0.488875 0.428836 1.413451 -0.683677 C -0.243064 -0.069446 -0.911166 0.478370
Option 1: adding result of division: bar / baz as a new foo column
In [222]: df = df.join(df[['bar']].div(df['baz']).rename(columns={'bar':'foo'})) In [223]: df Out[223]: first bar baz foo second one two one two one two A -1.089798 2.053026 0.470218 1.440740 -2.317647 1.424980 B 0.488875 0.428836 1.413451 -0.683677 0.345873 -0.627250 C -0.243064 -0.069446 -0.911166 0.478370 0.266761 -0.145172
Option 2: adding multi-level column with three "sub-columns":
In [235]: df = df.join(pd.DataFrame(np.random.rand(3,3), ...: columns=pd.MultiIndex.from_product([['new'], ['one','two','three']]), ...: index=df.index)) In [236]: df Out[236]: first bar baz new second one two one two one two three A -1.089798 2.053026 0.470218 1.440740 0.274291 0.636257 0.091048 B 0.488875 0.428836 1.413451 -0.683677 0.668157 0.456931 0.227568 C -0.243064 -0.069446 -0.911166 0.478370 0.333824 0.363060 0.949672
