python - How do I turn a dataframe into a series of lists?

Question

I have had to do this several times and I'm always frustrated. I have a dataframe:

df = pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]], ['a', 'b'], ['A', 'B', 'C', 'D'])

print df

   A  B  C  D
a  1  2  3  4
b  5  6  7  8

I want to turn df into:

pd.Series([[1, 2, 3, 4], [5, 6, 7, 8]], ['a', 'b'])

a    [1, 2, 3, 4]
b    [5, 6, 7, 8]
dtype: object

I've tried

df.apply(list, axis=1)

Which just gets me back the same df

What is a convenient/effective way to do this?

Answer 1

You can first convert DataFrame to numpy array by values, then convert to list and last create new Series with index from df if need faster solution:

print (pd.Series(df.values.tolist(), index=df.index))
a    [1, 2, 3, 4]
b    [5, 6, 7, 8]
dtype: object

Timings with small DataFrame:

In [76]: %timeit (pd.Series(df.values.tolist(), index=df.index))
1000 loops, best of 3: 295 μs per loop

In [77]: %timeit pd.Series(df.T.to_dict('list'))
1000 loops, best of 3: 685 μs per loop

In [78]: %timeit df.T.apply(tuple).apply(list)
1000 loops, best of 3: 958 μs per loop

and with large:

from string import ascii_letters
letters = list(ascii_letters)
df = pd.DataFrame(np.random.choice(range(10), (52 ** 2, 52)),
                  pd.MultiIndex.from_product([letters, letters]),
                  letters)

In [71]: %timeit (pd.Series(df.values.tolist(), index=df.index))
100 loops, best of 3: 2.06 ms per loop

In [72]: %timeit pd.Series(df.T.to_dict('list'))
1 loop, best of 3: 203 ms per loop

In [73]: %timeit df.T.apply(tuple).apply(list)
1 loop, best of 3: 506 ms per loop