BUG: Using .loc raises SettingWithCopyWarning

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Code Sample, a copy-pastable example

# Your code here
res = pd.DataFrame({"Method": ["Alpha1", "Beta1", "Beta2", "Alpha2", "Alpha3"], "Value": [5, 6, 7, 8, 10]})
df = res[res["Value"] <= 8]
df.loc[df["Method"].str.contains("Alpha"), "Method"] = "Gamma"

display(res)
display(df)

Problem description

In the code above, we are:

1. Creating a new dataframe res
2. Getting a copy of the dataframe where values are less than 8 and assigning that to df
3. Setting values in df using the .loc indexing

Step 3 raises the SettingWithCopyWarning. I don't believe we are setting the value of a copy there as we are using the .loc indexing method, which should set values in df. The values are being set, but the warning is being raised. If I'm understand the warning correctly, it should not be raised.

Expected Output

No warning should be raised

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 2cb9652
python : 3.7.9.final.0
python-bits : 64
OS : Linux
OS-release : 5.8.0-50-generic
Version : #56~20.04.1-Ubuntu SMP Mon Apr 12 21:46:35 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.2.4
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20200814
Cython : None
pytest : 6.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : 0.8.7
xarray : None
xlrd : None
xlwt : None
numba : 0.51.1

[Liam3851]

df = res[res["Value"] <= 8]

does not (necessarily) create a copy, it (at least can) create a view on res, hence the warning. SettingWithCopyWarning is in place specifically to catch this use case.

[attack68]

if you remove df from your code and just run:

res = pd.DataFrame({"Method": ["Alpha1", "Beta1", "Beta2", "Alpha2", "Alpha3"], "Value": [5, 6, 7, 8, 10]})
res[res["Value"] <= 8].loc[res[res["Value"] <= 8]["Method"].str.contains("Alpha"), "Method"] = "Gamma"

you get the same warning.

As @Liam3851 states you are not necessarily creating a copy.

The error goes away if you explicitly create a copy.

df = res[res["Value"] <= 8].copy()

[jreback]

pls read the https://pandas.pydata.org/docs/user_guide/indexing.html#indexing-view-versus-copy

this is virtually the same example.