[FIXED] DataFrame stores column of object as NaNs

Issue

DataFrame stores NaNs instead of column of vectors

df = pd.DataFrame({"a": [1,2,3], "b": [4,5,6]}, index=["one", "two", "three"])
s = pd.Series([(i*10, i*11, i*12) for i in df["a"]], dtype=object)

Here the series is what I need it to be (contains a vectors). But putting it together it only stores NaNs

df.loc[:, "c"] = s
#       a   b   c
#one    1   4   NaN
#two    2   5   NaN
#three  3   6   NaN

Solution

If indices are not exactly same in Series and DataFrame got NaNs, because indices don't align.

Solution is same indices in s.index like df.index:

s = pd.Series([v / np.linalg.norm(v) for v in maxShear_vec],dtype='object'),index=df.index)

df["maxShear_vec"] = s

Also I think dtype='object' should be omited:

s = pd.Series([v / np.linalg.norm(v) for v in maxShear_vec],index=df.index)

df["maxShear_vec"] = s

Answered By - jezrael