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I"d like to replace bad values in a column of a dataframe by NaN"s.

```
mydata = {"x" : [10, 50, 18, 32, 47, 20], "y" : ["12", "11", "N/A", "13", "15", "N/A"]}
df = pd.DataFrame(mydata)
df[df.y == "N/A"]["y"] = np.nan
```

Though, the last line fails and throws a warning because it"s working on a copy of df. So, what"s the correct way to handle this? I"ve seen many solutions with iloc or ix but here, I need to use a boolean condition.

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Moscow | 2023-02-08

I was preparing for my coding interview, thanks for clarifying this - How to set a cell to NaN in a pandas dataframe in Python is not the simplest one. I am just not quite sure it is the best method

Texas | 2023-02-08

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London | 2023-02-08

Thanks for explaining! I was stuck with How to set a cell to NaN in a pandas dataframe for some hours, finally got it done 🤗. I am just not quite sure it is the best method