Inconsistent SettingWithCopyWarning behavior
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---


#### Code Sample, a copy-pastable example

```python
import numpy as np
import pandas as pd

def example_1():
   df = pd.DataFrame(dict(x=np.arange(100), y=np.arange(100)))
   df_ = df[pd.Series([True] * 50 + [False] * 50, name="y")]
   df_.x *= 2

def example_2():
   df = pd.DataFrame(dict(x=np.arange(100), y=np.arange(100)))
   df_ = df[df.y < 50]
   df_.x *= 2

def example_3():
   df = pd.DataFrame(dict(x=np.arange(100), y=np.arange(100)))
   df_ = df[(df.y < 50) | (np.random.random(100) < 0.5)]
   df_.x *= 2

```

#### Problem description

Examples 2 and 3 above show (example 1 doesn't):

```
/usr/local/lib/python3.8/site-packages/pandas/core/generic.py:5170: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
```

I'm failing to see how 2 is different to 1 and how the behavior in 2 is so sticky than even adding a random mask isn't enough to stop it.

I believe that 1 and 2 should behave the same way and, if not, this extremely surprising behavior should at least be clarified in the documentation.

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

<details>


INSTALLED VERSIONS
------------------
commit           : b5958ee1999e9aead1938c0bba2b674378807b3d
python           : 3.8.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.1.0
Version          : Darwin Kernel Version 20.1.0: Sat Oct 31 00:07:11 PDT 2020; root:xnu-7195.50.7~2/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8

pandas           : 1.1.5
numpy            : 1.19.4
pytz             : 2020.4
dateutil         : 2.8.1
pip              : 20.3.1
setuptools       : 49.2.1
Cython           : 0.29.21
pytest           : 6.1.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.4
sqlalchemy       : 1.3.20
tables           : None
tabulate         : 0.8.7
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
