using .loc[row_indexer,col_indexer] = value does not allow to change the values I want to modify

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I tried to change some of the cells of a dataframe but I still get the SettingWithCopyWarning without replacing what I want. In effect with:

df.loc[df["subject"]!="subject1"]["Activity"] = np.nan

I got:

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: 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

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  """Entry point for launching an IPython kernel.

And when I tried to visualize this, nothing has changed:

161280     0
161281     0
161282     0
161283     0
161284     0
          ..
1215740    0
1215741    0
1215742    0
1215743    0
1215744    0
Name: Activity, Length: 1054465, dtype: int64
pandas python-3.x
1 Answers

modify it as follows, the value being set should be specified within loc. refer to pd.dataframe.loc

df.loc[df["subject"]!="subject1", "Activity"] = np.nan
userCaFe0
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