is_file_like requirements are too strict for boto3 S3 objects
#### Code Sample, a copy-pastable example if possible

```python
my_s3_object = boto3.client('s3').get_object(Bucket=<S3 bucket>, Key=<S3 path>)
pd.read_csv(my_s3_object['Body'])
```
#### Problem description

When trying to read csv files from AWS S3 directly using boto3, the returned botocore.response. StreamingBody object does not have all the neccessary methods required in is_file_like function of  pandas.core.dtypes.inference package. Although the pd.read_csv call worked flawlessly before, since the commit 20 days ago ( https://github.com/pandas-dev/pandas/commit/e4e87ec55765d31e59e97d89c71ed5a3fa2f3d38 ) our app is broken.

See botocore reference ( http://botocore.readthedocs.io/en/latest/reference/response.html ) for details on the StreamingBody class.

The issue is caused by the too strict constraint in is_file_like function ( https://github.com/pandas-dev/pandas/blob/master/pandas/core/dtypes/inference.py#L140 )

#### Expected Output

No error should be raised if read method is available on read operations.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Darwin
OS-release: 16.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.0rc1
pytest: 3.0.7
pip: 9.0.1
setuptools: 35.0.1
Cython: None
numpy: 1.12.0
scipy: 0.19.0
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
