Convert Python dict into a dataframe

I have a Python dictionary like the following:

    {u'2012-06-08': 388,
     u'2012-06-09': 388,
     u'2012-06-10': 388,
     u'2012-06-11': 389,
     u'2012-06-12': 389,
     u'2012-06-13': 389,
     u'2012-06-14': 389,
     u'2012-06-15': 389,
     u'2012-06-16': 389,
     u'2012-06-17': 389,
     u'2012-06-18': 390,
     u'2012-06-19': 390,
     u'2012-06-20': 390,
     u'2012-06-21': 390,
     u'2012-06-22': 390,
     u'2012-06-23': 390,
     u'2012-06-24': 390,
     u'2012-06-25': 391,
     u'2012-06-26': 391,
     u'2012-06-27': 391,
     u'2012-06-28': 391,
     u'2012-06-29': 391,
     u'2012-06-30': 391,
     u'2012-07-01': 391,
     u'2012-07-02': 392,
     u'2012-07-03': 392,
     u'2012-07-04': 392,
     u'2012-07-05': 392,
     u'2012-07-06': 392}

The keys are Unicode dates and the values are integers. I would like to convert this into a pandas dataframe by having the dates and their corresponding values as two separate columns. Example: col1: Dates col2: DateValue (the dates are still Unicode and datevalues are still integers)

         Date         DateValue
    0    2012-07-01    391
    1    2012-07-02    392
    2    2012-07-03    392
    .    2012-07-04    392
    .    ...           ...
    .    ...           ...

Any help in this direction would be much appreciated. I am unable to find resources on the pandas docs to help me with this.

I know one solution might be to convert each key-value pair in this dict, into a dict so the entire structure becomes a dict of dicts, and then we can add each row individually to the dataframe. But I want to know if there is an easier way and a more direct way to do this.

So far I have tried converting the dict into a series object but this doesn't seem to maintain the relationship between the columns:

    s  = Series(my_dict,index=my_dict.keys())

The error here, is since calling the DataFrame constructor with scalar values (where it expects values to be a list/dict/... i.e. have multiple columns):

    pd.DataFrame(d)
    ValueError: If using all scalar values, you must must pass an index

You could take the items from the dictionary (i.e. the key-value pairs):

    In [11]: pd.DataFrame(d.items())  # or list(d.items()) in python 3
    Out[11]:
                 0    1
    0   2012-07-02  392
    1   2012-07-06  392
    2   2012-06-29  391
    3   2012-06-28  391
    ...

    In [12]: pd.DataFrame(d.items(), columns=['Date', 'DateValue'])
    Out[12]:
              Date  DateValue
    0   2012-07-02        392
    1   2012-07-06        392
    2   2012-06-29        391

But I think it makes more sense to pass the Series constructor:

    In [21]: s = pd.Series(d, name='DateValue')
    Out[21]:
    2012-06-08    388
    2012-06-09    388
    2012-06-10    388

    In [22]: s.index.name = 'Date'

    In [23]: s.reset_index()
    Out[23]:
              Date  DateValue
    0   2012-06-08        388
    1   2012-06-09        388
    2   2012-06-10        388

From: stackoverflow.com/q/18837262