Store numpy.array in cells of a Pandas.DataFrame

Question

I have a dataframe in which I would like to store 'raw' numpy.array:

df['COL_ARRAY'] = df.apply(lambda r: np.array(do_something_with_r), axis=1) 

but it seems that pandas tries to 'unpack' the numpy.array.

Is there a workaround? Other than using a wrapper (see edit below)?

I tried reduce=False with no success.

EDIT

This works, but I have to use the 'dummy' Data class to wrap around the array, which is unsatisfactory and not very elegant.

class Data:     def __init__(self, v):         self.v = v  meas = pd.read_excel(DATA_FILE) meas['DATA'] = meas.apply(     lambda r: Data(np.array(pd.read_csv(r['filename'])))),     axis=1 ) 

Answer 1

Use a wrapper around the numpy array i.e. pass the numpy array as list

a = np.array([5, 6, 7, 8]) df = pd.DataFrame({"a": [a]}) 

Output:

              a 0  [5, 6, 7, 8] 

Or you can use apply(np.array) by creating the tuples i.e. if you have a dataframe

df = pd.DataFrame({'id': [1, 2, 3, 4],                    'a': ['on', 'on', 'off', 'off'],                    'b': ['on', 'off', 'on', 'off']})  df['new'] = df.apply(lambda r: tuple(r), axis=1).apply(np.array) 

Output :

      a    b  id            new 0   on   on   1    [on, on, 1] 1   on  off   2   [on, off, 2] 2  off   on   3   [off, on, 3] 3  off  off   4  [off, off, 4] 

df['new'][0] 

Output :

array(['on', 'on', '1'], dtype='<U2')