SettingWithCopyWarning single- vs mixed-type dataframes
#### Problem description

It seems that pandas (at least `v0.23.4`) handles mixed-type and single-type dataframes differently when it comes to throwing `SettingWithCopyWarning`

```python
    df = pd.DataFrame({'a': [4, 5, 6], 'c': [3, 2, 1]})
    df._is_view # False
    df._is_cached # False
    df._is_mixed_type # False

    df.iloc[-1]['c'] = 42 # no warning
```
```python
    df = pd.DataFrame({'a': ['x', 'y', 'z'], 'c': ['t', 'u', 'v']})
    df._is_view # False
    df._is_cached # False
    df._is_mixed_type # False

    df.iloc[-1]['c'] = 'f' # no warning
```
```python
    df = pd.DataFrame({'a': ['x', 'y', 'z'], 'c': [3, 2, 1]})
    df._is_view # False
    df._is_cached # False
    df._is_mixed_type # True

    df.iloc[-1]['c'] = 42 # SettingWithCopyWarning: ...
```

#### Expected Output

`SettingWithCopyWarning` should appear in all three cases above.

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

<details>
INSTALLED VERSIONS

commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-38-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8

pandas: 0.23.4
pytest: 3.2.1
pip: 18.0
setuptools: 40.2.0
Cython: 0.26.1
numpy: 1.13.3
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.5.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.7.3
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 3.0.1
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.1.13
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>
