pandas - Append a tuple to a dataframe as a row -

i looking solution add rows dataframe. here data have : grouped object ( obtained grouping dataframe on month , year i.e in grouped object key [month,year] , value rows / dates in month , year).

i want extract month , year combinations , put in new dataframe. issue : when iterate on grouped object, month, row tuple, converted tuple list , added dataframe using thye append command. instead of getting added rows : 1 2014 2 2014 3 2014 got added in 1 column 0 1 1 2014 0 2 1 2014 0 3 1 2014 ...

i want store these values in new dataframe. here how want new dataframe : month year 1 2014 2 2014 3 2014

i tried converting tuple list , tried various other things pivoting. inputs helpful.

here sample code :

    df=df.groupby(['month','year'])     df = pd.dataframe()     key, value in df:             print "type of key is:",type(key)             print "type of list(key) is:",type(list(key))             df = df.append(list(key))     print df 

when groupby resulting multiindex available as:

in [11]: df = pd.dataframe([[1, 2014, 42], [1, 2014, 44], [2, 2014, 23]], columns=['month', 'year', 'val'])  in [12]: df out[12]:    month  year  val 0      1  2014   42 1      1  2014   44 2      2  2014   23  in [13]: g = df.groupby(['month', 'year'])  in [14]: g.grouper.result_index out[14]: multiindex(levels=[[1, 2], [2014]],            labels=[[0, 1], [0, 0]],            names=['month', 'year']) 

often sufficient, , won't need dataframe. if do, 1 way following:

in [21]: pd.dataframe(index=g.grouper.result_index).reset_index() out[21]:    month  year 0      1  2014 1      2  2014 

i thought there method this, can't recall it.

if want tuples can use .values or to_series:

in [31]: g.grouper.result_index.values out[31]: array([(1, 2014), (2, 2014)], dtype=object)  in [32]: g.grouper.result_index.to_series() out[32]: month  year 1      2014    (1, 2014) 2      2014    (2, 2014) dtype: object