python - numpy arrays dimension mismatch -

i using numpy , pandas attempt concatenate number of heterogenous values single array.

np.concatenate((tmp, id, freqs)) 

here exact values:

tmp = np.array([u'dnmt3a', u'p.m880v', u'chr2', 25457249], dtype=object) freqs = np.array([0.022831050228310501], dtype=object) id = "id_23728" 

the dimensions of tmp, 17232, , freqs follows:

[in]  tmp.shape [out] (4,) [in]  np.array(17232).shape [out] () [in]  freqs.shape [out] (1,) 

i have tried casting them numpy arrays no avail.

although variable freqs have more 1 value.

however, both np.concatenate , np.append functions following error:

*** valueerror: input arrays must have same number of dimensions 

these have same number of columns (0), why can't concatenate them either of above described numpy methods?

all i'm looking obtain is[(tmp), 17232, (freqs)] in 1 single dimensional array, appended onto end of pandas dataframe.

thanks.

update

it appears can concatenate 2 existing arrays:

np.concatenate([tmp, freqs],axis=0) array([u'dnmt3a', u'p.m880v', u'chr2', 25457249, 0.022831050228310501], dtype=object) 

however, integer, when casted cannot used in concatenate.

np.concatenate([tmp, np.array(17571)],axis=0) *** valueerror: input arrays must have same number of dimensions 

what work, nesting append , concatenate

np.concatenate((np.append(tmp, 17571), freqs),) array([u'dnmt3a', u'p.m880v', u'chr2', 25457249, 17571,        0.022831050228310501], dtype=object) 

although kind of messy. have better solution concatenating number of heterogeneous arrays?

the problem id, , later integer np.array(17571), not array_like object. see here how numpy decides whether object can converted automatically numpy array or not.

the solution make id array_like, i.e. element of list or tuple, numpy understands id belongs 1d array_like structure

it boils down to

concatenate((tmp, (id,), freqs)) 

or

concatenate((tmp, [id], freqs)) 

to avoid sort of problems when dealing input variables in functions using numpy, can use atleast_1d, pointed out @askewchan. see this question/answer.

basically, if unsure if in different scenarios variable id single str or list of str, better off using

concatenate((tmp, atleast_1d(id), freqs)) 

because 2 options above fail if id list/tuple of strings.

edit: may not obvious why np.array(17571) not array_like object. happens because np.array(17571).shape==(), not iterable has no dimensions.