I've got a dataframe with a multi index of Year and Month like the following
| |Value
Year |Month|
| 1 | 3
1992 | 2 | 5
| 3 | 8
| ... | ...
1993 | 1 | 2
| ... | ...
I'm trying to select the maximum Value for each year and put that in a DF like this:
| Max
Year |
1992 | 5
1993 | 2
| ...
There's not much info on multi-indexes, should I simply do a group by and apply or something similar to make it more simple?
Exactly right:
df.groupby(level=0).apply(max)
In my sample DataFrame
:
0 Caps Lower A a 0 0.246490 1 -1.265711 2 -0.477415 3 -0.355812 4 -0.724521 b 0 -0.409198 1 -0.062552 2 -0.731789 3 1.131616 4 0.085248 B a 0 0.193948 1 2.010710 2 0.289300 3 0.305373 4 1.376965 b 0 0.210522 1 1.431279 2 -0.247171 3 0.899074 4 0.639926
Result:
0 Caps A 1.131616 B 2.010710
This is how I created the DataFrame
, by the way:
df = pd.DataFrame(np.random.randn(5,4), columns = l)
df.columns = pd.MultiIndex.from_tuples(df.columns, names=['Caps','Lower'])
df = pd.DataFrame(df.unstack())