df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
...                          "bar", "bar", "bar", "bar"],
...                    "B": ["one", "one", "one", "two", "two",
...                          "one", "one", "two", "two"],
...                    "C": ["2017", "2017", "2018", "2017",
...                          "2018", "2017", "2018", "2017",
...                          "2017"],
...                    "D": [1, 2, 2, 3, 3, 4, 5, 6, 7]})
dataf = df.pivot_table(values="D", index=["A","B"], columns=["C"], aggfunc=np.sum, margins=True, dropna=True)
dataf
C       2017    2018    All
A   B
bar one 4.0     5.0     9
two     13.0    NaN    13
foo one 3.0     2.0     5
two     3.0     3.0     6
All     23.0    10.0   33

In [71]: dataf['new'] = dataf['2018'] / dataf['2017']

In [72]: dataf
Out[72]:
C        2017  2018  All       new
A   B
bar one   4.0   5.0    9  1.250000
    two  13.0   NaN   13       NaN
foo one   3.0   2.0    5  0.666667
    two   3.0   3.0    6  1.000000
All      23.0  10.0   33  0.434783