The most straightforward way is with .loc: >>> data.loc[:, ([‘one’, ‘two’], [‘a’, ‘b’])] one two a b a b 0 0.4 -0.6 -0.7 0.9 1 0.1 0.4 0.5 -0.3 2 0.7 -1.6 0.7 -0.8 3 -0.9 2.6 1.9 0.6 Remember that [] and () have special meaning when dealing with a MultiIndex object: (…) a … Read more
There is a get_level_values method that you can use in conjunction with boolean indexing to get the the intended result. In [13]: df = pd.DataFrame(np.random.random((4,4))) df.columns = pd.MultiIndex.from_product([[1,2],[‘A’,’B’]]) print df 1 2 A B A B 0 0.543980 0.628078 0.756941 0.698824 1 0.633005 0.089604 0.198510 0.783556 2 0.662391 0.541182 0.544060 0.059381 3 0.841242 0.634603 0.815334 … Read more
You’re getting the error because result defined as Sequential() is just a container for the model and you have not defined an input for it. Given what you’re trying to build set result to take the third input x3. first = Sequential() first.add(Dense(1, input_shape=(2,), activation=’sigmoid’)) second = Sequential() second.add(Dense(1, input_shape=(1,), activation=’sigmoid’)) third = Sequential() # … Read more