apply converting dtypes of arguments
#### Code Sample, a copy-pastable example if possible
In this snippet of code:

```python
# Your code here
def pwr_offset (n_streams, delta):
    #print ('n_streams:', n_streams, 'delta:', delta)
    return 10 * log10 (np.sum (10**(-0.1*e) for e in find_pwr_offsets (n_streams, delta)))

df['esno_correction2'] = df[['n_streams', 'stream_pwr_offset']].apply(lambda x: pwr_offset (x[0], x[1]), axis=1)

```

df['n_streams'] has type int, while df['stream_pwr_offset'] has type float.  I find the type passed to pwr_offset for 1st arg is converted int->float.  I didn't expect or want that.

#### Problem description

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution.]

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#### Expected Output

#### Output of ``pd.show_versions()``
I
<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.16.14-300.fc28.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.21.0
pytest: 3.4.2
pip: 9.0.3
setuptools: 40.0.0
Cython: 0.27.3
numpy: 1.14.5
scipy: 1.0.1
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.7.5
patsy: 0.4.1
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.2.2
openpyxl: 2.4.9
xlrd: 1.1.0
xlwt: 1.1.2
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.2.10
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.6.0


</details>
