Pandas: customed aggregate functions for DataFrameGroupBy - python-3.x

Question

I have the following data frame my_df:
name date A_score B_score
------------------------------------------
John 2017-01-01 5 6
John 2017-01-10 10 8
John 2017-02-04 3 5
Andy 2017-01-25 8 9
Andy 2017 02-05 7 1
Andy 2017-02-12 9 9
For each name, we want to find the absolute delta of A_score and B_score. The absolute delta is defined as the absolute value difference between the earliest date and the second earliest date.
The resulting data frame should be like:
name A_score_result B_score_result
----------------------------------------------
John 5 2
Andy 1 8
To achieve this, I tried:
new_df = my_df.groupby('name').apply(lambda x:myFun(x))
and
new_df = my_df.groupby('name').agg(['myFun'])
where myFun is:
def myFun(x):
y = x[2]-x[1]
return y
However, both approaches have errors like below:
/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in __getitem__(self, key)
2057 return self._getitem_multilevel(key)
2058 else:
-> 2059 return self._getitem_column(key)
2060
2061 def _getitem_column(self, key):
/usr/local/lib/python3.4/dist-packages/pandas/core/frame.py in _getitem_column(self, key)
2064 # get column
2065 if self.columns.is_unique:
-> 2066 return self._get_item_cache(key)
2067
2068 # duplicate columns & possible reduce dimensionality
/usr/local/lib/python3.4/dist-packages/pandas/core/generic.py in _get_item_cache(self, item)
1384 res = cache.get(item)
1385 if res is None:
-> 1386 values = self._data.get(item)
1387 res = self._box_item_values(item, values)
1388 cache[item] = res
/usr/local/lib/python3.4/dist-packages/pandas/core/internals.py in get(self, item, fastpath)
3541
3542 if not isnull(item):
-> 3543 loc = self.items.get_loc(item)
3544 else:
3545 indexer = np.arange(len(self.items))[isnull(self.items)]
/usr/local/lib/python3.4/dist-packages/pandas/indexes/base.py in get_loc(self, key, method, tolerance)
2134 return self._engine.get_loc(key)
2135 except KeyError:
-> 2136 return self._engine.get_loc(self._maybe_cast_indexer(key))
2137
2138 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4145)()
pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4009)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13166)()
pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13120)()
KeyError: 0
Any suggestion on how to fix this problem? Thanks a lot!

Answer 1

Try this:
In [358]: df.drop('date',1).groupby('name').agg(lambda x: abs(x.iloc[1] - x.iloc[0]))
Out[358]:
A_score B_score
name
Andy 1 8
John 5 2