groupby.apply make additional operation.
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
tt=[]

def func(x):
    tt.append(x.B.iloc[0])
    return 1
df = pd.DataFrame({'A': [1,1,1,1,1,2,2,2,2], 'B': [0,1,2,3,4,5,6,7,8]})
df.groupby('A').apply(func)
tt

#### [0, 0, 5]

```
#### Problem description

the list 'tt' should be [0, 5], but the first group applied twice and  'tt' become [0, 0, 5].
so is it a bug here?

For documentation-related issues, you can check the latest versions of the docs on `master` here:

https://pandas-docs.github.io/pandas-docs-travis/

If the issue has not been resolved there, go ahead and file it in the issue tracker.

#### Expected Output
[0,5]
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-514.16.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: zh_CN.UTF-8
LOCALE: zh_CN.UTF-8

pandas: 0.22.0
pytest: 3.0.7
pip: 9.0.1
setuptools: 38.5.1
Cython: 0.27.3
numpy: 1.14.1
scipy: 1.0.0
pyarrow: 0.8.0
xarray: 0.10.0
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: 0.4.0
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 1.0.0
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.5.0
</details>
