Append another column values to pandas column with list values

Question

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.

SeaBean · Accepted Answer · 2021-09-23 08:53:03Z

1

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)

answered Sep 23, 2021 at 8:53

SeaBean

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1 Comment

Tharsalys Over a year ago

Thank you, it worked. For future viewers, I'll add that if you want to add more columns like this, you can try : df.apply(lambda x: np.append(x['a'], (x['b'], x['c'])), axis=1).to_numpy()

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