read_csv / read_excel interpret str as datetime
#### Code Sample
```python

df2 = pd.read_excel('license_nvm_logins.xlsx', sheet_name='Common', dtype={'Total Usage':str})
df2.head(n=10)
```

```python
df2.dtypes()

User Name                object
Feature Name             object
Tag                      object
Machine Name             object
Checkout Date    datetime64[ns]
Checkout Time            object
Total Usage              object
```
#### Problem description
When I read my Excel- / CSV-File into a DataFrame the last column 'Total Usage' will be interpreted as datetime (even if I try to force it to stay as a string).
This happens if the %H part exceeds 24 hours. For instance if the content of 'Total Usage'
column has following content '54:05:03'

User Name | Feature Name | Tag | Machine Name | Checkout Date | Checkout Time | Total Usage
-- | -- | -- | -- | -- | -- | --
someUser| someFeature | someTag | someMachine | 13.09.2018 | 07:40:00 | 1900-01-02 06:05:03

#### Expected Output
I would like if that columns would stay as string so I've the option to parse it to a timedelta on my own.

User Name | Feature Name | Tag | Machine Name | Checkout Date | Checkout Time | Total Usage
-- | -- | -- | -- | -- | -- | --
someUser| someFeature | someTag | someMachine | 13.09.2018 | 07:40:00 | 54:05:03

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-87-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.4.2
pip: 19.0.2
setuptools: 39.0.1
Cython: 0.27.3
numpy: 1.14.3
scipy: 1.0.1
pyarrow: 0.9.0
xarray: 0.10.7
IPython: 6.3.1
sphinx: 1.7.1
patsy: 0.5.0
dateutil: 2.7.2
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.2.2
openpyxl: 2.5.1
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.2.0
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.5
pymysql: None
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
