How to convert pandas framework to one-dimensional array?

Question

I have a dataframe X. I want to convert it to a 1D array with 5 elements. One way to do this is to convert internal arrays to lists. How can i do this?

      0 1 2 3 4 5
0 1622 95 1717 85.278544 1138.964373 1053.685830
1 62 328 390 75.613900 722.588235 646.974336
2 102 708 810 75.613900 800.916667 725.302767
3 102 862 964 75.613900 725.870370 650.256471
4 129 1380 1509 75.613900 783.711111 708.097211

val = X.valueswill provide a numpy array. I want to convert the internal elements of an array to a list. How can i do this? I tried this but could not

M = val.values.tolist()
A = np.array(M,dtype=list)
N = np.array(M,dtype=object)

Answer 1

, , 1D -

In [231]: df
Out[231]: 
      0     1     2          3            4            5
0  1622    95  1717  85.278544  1138.964373  1053.685830
1    62   328   390  75.613900   722.588235   646.974336
2   102   708   810  75.613900   800.916667   725.302767
3   102   862   964  75.613900   725.870370   650.256471
4   129  1380  1509  75.613900   783.711111   708.097211

In [232]: out = np.empty(df.shape[0], dtype=object)

In [233]: out[:] = df.values.tolist()

In [234]: out
Out[234]: 
array([list([1622.0, 95.0, 1717.0, 85.278544, 1138.964373, 1053.6858300000001]),
       list([62.0, 328.0, 390.0, 75.6139, 722.5882349999999, 646.974336]),
       list([102.0, 708.0, 810.0, 75.6139, 800.916667, 725.302767]),
       list([102.0, 862.0, 964.0, 75.6139, 725.87037, 650.256471]),
       list([129.0, 1380.0, 1509.0, 75.6139, 783.7111110000001, 708.097211])], dtype=object)

In [235]: out.shape
Out[235]: (5,)

In [236]: out.ndim
Out[236]: 1

Answer 2

df.as_matrix(), ?

EDIT:

:

L=[]
for m in df.as_matrix().tolist():
    L += m