Why read_sas is converting strings to float?
#### Code Sample
```python
import pandas as pd
df = pd.read_sas('test.sas7bdat', format='sas7bdat', encoding='utf-8')

```
#### Problem description

I am trying to read a `.sas7bdat` file using `read_sas` and I am having a hard time because the module is converting strings values that look like a number into `float`.

For example, if I have a telephone number like `'348386789'` and I read it with the code I posted the output obtained is `348386789.0`.

I noticed the same problem in the `read_csv` function but there you can use the argument `dtype` to manually set the type for each column (es. dtype={'number': str)}).

#### Expected Output

`'348386789'`

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

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.2.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: None
pip: 19.1.1
setuptools: 41.0.0
Cython: None
numpy: 1.16.3
scipy: None
pyarrow: 0.13.0
xarray: None
IPython: 7.4.0
sphinx: 2.1.2
patsy: None
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: 3.5.2
numexpr: 2.6.9
feather: 0.4.0
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.3.4
bs4: None
html5lib: None
sqlalchemy: 1.3.5
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
