python - I want to filter out a non-numeric value and calculate it's new value using two other columns in the dataframe (pandas)

Question

I have a df that looks something like this:

col1	col2	col3
0.8	0.1	SP
0.9	0	SP
0.9	0.1	SP
0.7	SP	0.2
0.9	SP	0

Answer 1

This look like no reliable code, but still it could help.

df[df['col3']=='SP'] do the same as df.loc[df['col3']=='SP'], but 'df.loc' should be better for assigning. (when you try without .loc it will recommend use it for assign)

The code filter the rows where SP is in column 3, then assign.

df['col3'].loc[df['col3']=='SP']=1-df['col1'][df['col3']=='SP']-df['col2'][df['col3']=='SP']

EDIT

*Alternatives: 5 ways to apply an IF condition in Pandas DataFrame

df['col3']=df.apply(lambda x: 1-x['col1']-x['col2'] if x['col3'] == 'SP' else x['col3'],axis=1)