Say I have a dataframe with negative values on specific columns:

df = pd.DataFrame([[1, 1, -1],[-1, 1, 1],[-1, -1, 1]])

Now, I want to inplace clip the negative values to 0 on only specific lines and columns:

df.loc[[1, 2], [0, 1]].clip(lower=0, inplace=True)

But this doesn't work:

df
Out: 
   0  1  2
0  1  1 -1
1 -1  1  1
2 -1 -1  1

This is because slicing dataframe with a list of integers returns a copy:

df.loc[[1, 2], [0, 1]] is df.loc[[1, 2], [0, 1]]
Out: False

How do I make inplace changes to specific rows and columns then?

CodePudding user response：

How about using df.lt instead:

df[df.loc[[1, 2], [0, 1]].lt(0)] = 0

print(df)

   0  1  2
0  1  1 -1
1  0  1  1
2  0  0  1

CodePudding user response：

You can do this:

df.loc[[1, 2], [0, 1]] = df.loc[[1, 2], [0, 1]].clip(lower=0)

Output:

   0  1  2
0  1  1 -1
1  0  1  1
2  0  0  1