I have a DataFrame with 200 columns.
Some of the rows in columns between 10 and 180 have values between -1 and 0.
I need to remove all rows with these values, but only if they occur in columns between 100 and 180. If these values occur in columns 10 to 99 it is fine and I keep them.
I was thinking to use something like:
df[~df[['col100', 'col101',..., 'col180']].isin([-1, 0]).any(1)]
However, I cannot specify all the column names by hand. What is the right way to do this operation?
Use loc accessor
If you need between -1 and 0, use;
df[~df.loc[:,'col100':'col180'].apply(lambda x: x.between(-1,0)).any(1)]
If you need just to check if they have -1 and 0 use
df[~df.loc[:,'col100':'col180'].isin([0,-1]).any(1)]
How it works
df.loc[:,'col100':'col180']- Selects the columns between 100 and 180
df.loc[:,'col100':'col180'].isin([0,-1]).any(1): Tests if there is 0 or -1 in the columns
How about
cols_to_remove = [f'col{n}' for n in range(100,181)]
df[~df[cols_to_remove].isin([-1, 0]).any(1)]
