On Friday, 6 September 2019 07:52:56 UTC+10, Piet van Oostrum wrote: > Piet van Oostrum <> writes: > > > That would select ROWS 0,1,5,6,7, not columns. > > To select columns 0,1,5,6,7, use two-dimensional indexes > > > > df1 = df.iloc[:, [0,1,5,6,7]] > > > > : selects all rows. > > And that also solves your original problem. > > This statement: > > df1['Difference'] = df1.loc['Current Team'].str.lower().str.strip() == > df1.loc['New Team'].str.lower().str.strip() > > should not use .loc, because then you are selecting rows, not columns, but: > > df1['Difference'] = df1['Current Team'].str.lower().str.strip() == df1['New > Team'].str.lower().str.strip() > -- > Piet van Oostrum <> > WWW: http://piet.vanoostrum.org/ > PGP key: [8DAE142BE17999C4]
That actually creates another error. A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy So tried this df['c'] = df.apply(lambda df1: df1['Current Team'].str.lower().str.strip() == df1['New Team'].str.lower().str.strip(), axis=1) Based on this SO answer https://stackoverflow.com/a/46570641 Thoughts? Sayth -- https://mail.python.org/mailman/listinfo/python-list
