BUG: field in Series produced by DataFrame.iterrows  has type Timestamp instead of string
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
from datetime import datetime

df = []
df.append({
    'a': '1801',
    'b': datetime.now(),    
})
df.append({
    'a': '11801',
    'b': datetime.now(),    
})
df = pd.DataFrame(df)

for i, row in df.iterrows():
    print(row['a'], type(row['a']))
```
#### Problem description

Series, which were produced by DataFrame.iterrows has wrong data type. String field was converted to pandas.Timestamp.

For the first row, str was converted to Timestamp.
```pandas
1801-01-01 00:00:00 <class 'pandas._libs.tslibs.timestamps.Timestamp'>
11801 <class 'str'>
```

#### Expected Output
```pandas
1801   <class 'str'>
11801 <class 'str'>
```

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: 4.5.0
pip: 19.1.1
setuptools: 41.0.1
Cython: None
numpy: 1.16.3
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.5.0
sphinx: None
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.3
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: None
bs4: None
html5lib: None
sqlalchemy: 1.3.3
pymysql: None
psycopg2: 2.7.6.1 (dt dec pq3 ext lo64)
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

</details>
