Pandas DENSE RANK

You can convert the year to categoricals and then take their codes (adding one because they are zero indexed and you wanted the initial value to start with one per your example).

df['Rank'] = df.Year.astype('category').cat.codes + 1

>>> df
   Year  Value  Rank
0  2012     10     1
1  2013     20     2
2  2013     25     2
3  2014     30     3

Use pd.Series.rank with method='dense'

df['Rank'] = df.Year.rank(method='dense').astype(int)

df

The fastest solution is factorize:

df['Rank'] = pd.factorize(df.Year)[0] + 1

Timings:

#len(df)=40k
df = pd.concat([df]*10000).reset_index(drop=True)

In [13]: %timeit df['Rank'] = df.Year.rank(method='dense').astype(int)
1000 loops, best of 3: 1.55 ms per loop

In [14]: %timeit df['Rank1'] = df.Year.astype('category').cat.codes + 1
1000 loops, best of 3: 1.22 ms per loop

In [15]: %timeit df['Rank2'] = pd.factorize(df.Year)[0] + 1
1000 loops, best of 3: 737 µs per loop