Denoting duplicated by specific combination of index
#### Code Sample

```python
pandas.DataFrame.duplicated(subset=None, keep='first')
```
#### Problem description
Pandas have a built-in method for denoting duplicated records. However, it is not able to denote duplicated record by some combination of keys. 
**dataFrame a**
```
index1  index2  val1  val2
a      y      1      1
a      y      1      2
b      z      2      2
c      x      3      3
```

**dataFrame b**
```
index1  index2  val3
a      y      1
b      z      2
```
there are nodupkey for the first glance. 
but this could cause issues when performing merging with validate='1:1' criteria. 
```
pd.merge(a, b, validate='1:1')
```
we expect that both data set is unique by index1 and index2.
But in dataFrame a, the records are not unique which cause merging failed.
In SAS, duplicate in by group can be found by executing
```sas
proc sort data=sample nouniqueky out=dup; 
    by var1 var2; 
run;
```

#### Expected Output
Expected add a parameter such as `groupby or index`

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 69 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.21.1
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.13.3
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.5.0
</details>
