[python] Pandas DataFrame column to list

The above solution is good if all the data is of same dtype. Numpy arrays are homogeneous containers. When you do df.values the output is an numpy array. So if the data has int and float in it then output will either have int or float and the columns will loose their original dtype. Consider df

a  b 
0  1  4
1  2  5 
2  3  6 

a    float64
b    int64 

So if you want to keep original dtype, you can do something like

row_list = df.to_csv(None, header=False, index=False).split('\n')

this will return each row as a string.

['1.0,4', '2.0,5', '3.0,6', '']

Then split each row to get list of list. Each element after splitting is a unicode. We need to convert it required datatype.

def f(row_str): 
  row_list = row_str.split(',')
  return [float(row_list[0]), int(row_list[1])]

df_list_of_list = map(f, row_list[:-1])

[[1.0, 4], [2.0, 5], [3.0, 6]]