Since you're working on a project of a datamining nature, have you considered using Pandas instead?
Here's an example of how I can convert a list of tuples into a Pandas dataframe. I've highlighted a few common newbie errors I made when I first started out with Pandas, to give you an idea of what you can do and cannot do.
In [1]: import pandas as pd
In [2]: data = [(1, 2), (1, 5), (2, 3), (2, 2)]
In [3]: pd.datafr
In [3]: pd.DataFrame(data)
Out[3]:
0 1
0 1 2
1 1 5
2 2 3
3 2 2
In [4]: pd.columns[0] = 'column 1'
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-c313e6b0cb87> in <module>()
----> 1 pd.columns[0] = 'column 1'
AttributeError: 'module' object has no attribute 'columns'
In [5]: df = pd.DataFrame(data)
In [6]: df
Out[6]:
0 1
0 1 2
1 1 5
2 2 3
3 2 2
In [7]: df.columns
Out[7]: Int64Index([0, 1], dtype=int64)
In [8]: df.columns[1] = "column 2"
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-8-76ee806aec72> in <module>()
----> 1 df.columns[1] = "column 2"
/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas-0.12.0-py2.7-macosx-10.6-intel.egg/pandas/core/index.pyc in __setitem__(self, key, value)
328
329 def __setitem__(self, key, value):
--> 330 raise Exception(str(self.__class__) + ' object is immutable')
331
332 def __getitem__(self, key):
Exception: <class 'pandas.core.index.Int64Index'> object is immutable
In [9]: df.columns = ["column 1", "column 2"]
In [10]: df
Out[10]:
column 1 column 2
0 1 2
1 1 5
2 2 3
3 2 2
In [11]: exit()
Specifically with your example:
In [1]: import pandas as pd
In [3]: import datetime
In [4]: t1=[[datetime.datetime(2013, 10, 1, 20, 54, 51), 'last'],[datetime.datetime(2013, 8, 1, 20, 54, 51), 'First'],[datetime.datetime(2013, 9, 2, 20, 54, 51), 'second']]
In [5]: t1
Out[5]:
[[datetime.datetime(2013, 10, 1, 20, 54, 51), 'last'],
[datetime.datetime(2013, 8, 1, 20, 54, 51), 'First'],
[datetime.datetime(2013, 9, 2, 20, 54, 51), 'second']]
In [6]: df = pd.DataFrame(t1)
In [7]: df
Out[7]:
0 1
0 2013-10-01 20:54:51 last
1 2013-08-01 20:54:51 First
2 2013-09-02 20:54:51 second