Append another column values to pandas column with list values-CodePudding

I have a DataFrame that looks like:

              a   b
0  [1., 2., 3.]   1.
1  [4., 5., 6.]   2.

I want a 2d numpy array that takes the list from column a and appends values from column b, like so:

[[1., 2., 3., 1.],
 [4., 5., 6., 2.]]

I've tried unsuccessfully:

>>>np.c_[df.a, df.b]

array([[array([1., 2., 3.], dtype=float32), 1.],
      [[array([4., 5., 6.], dtype=float32), 2.]], dtype=object)

Variants of np.hstack or np.append lead to the same result.

CodePudding user response：

>>>df = pd.DataFrame(
    {
        'a':[np.array([1., 2., 3.]),np.array([4., 5., 6.])], 
        'b':[1., 2.]
        })
>>>df

               a    b
0   [1.0, 2.0, 3.0] 1.0
1   [4.0, 5.0, 6.0] 2.0

>>>df.apply(lambda x: np.append(x.a, x.b), axis=1).apply(pd.Series).values

array([[1., 2., 3., 1.],
       [4., 5., 6., 2.]])

CodePudding user response：

>>>df.apply(lambda x: x['a']   [x['b']], axis=1).apply(pd.Series).values

array([[1., 2., 3., 1.],
       [4., 5., 6., 2.]])

CodePudding user response：

You can use numpy.append with .apply(), as follows:

df.apply(lambda x:  np.append(x['a'], x['b']), axis=1).to_numpy()

Result:

array([array([1, 2, 3, 1]), 
       array([4, 5, 6, 2])], dtype=object)