I am cleaning a pandas dataframe imported from a .csv. It has useful data in the first and second columns, then junk in columns 3-5. This pattern repeats where every 5th column starting from the first and second columns are useful, and every 5th column starting from the third through fifth are junk. I can remove the junk columns using the code below: df1 = df.drop(columns=df.columns[4::5]) df1 = df1.drop(columns=df1.columns[3::4]) df1 = df1.drop(columns=df1.columns[2::3]) Is there a solution to do this all in one line? Continue reading...
