python - Assigning multiple pandas columns using list slice -

in python, possible assign multiple variables objects in list. possible same pandas dataframe example:

df.trinucleotide 0   aca  1   acc 2   acg 3   act 4   aca 5   acc 6   acg 7   act 8   aca 9   acc  df.loc[:,['first','second','third']] =  df.trinucleotide.apply(lambda x: list(x))  

this results in keyerror: "['first' 'second' 'third'] not in index" error while separating variables commas not work well.

df.loc[:,'first'], df.loc[:,'second'],df.loc[:,'third'] =  df.trinucleotide.apply(lambda x: list(x))  valueerror: many values unpack      

is there way without explicitly assigning each variable slice index of list?

to create multiple columns when using apply, think it's best return series rather list. can set column names setting them index series. can do:

# reading data in df = pd.read_clipboard(header=none, index_col=0) df.columns = ['trinucleotide'] df out[9]:    trinucleotide 0               0           aca 1           acc 2           acg # etc.  new_cols = df['trinucleotide'].apply(     lambda x: pd.series(list(x), index=['first', 'second', 'third']) ) df[['first', 'second', 'third']] = new_cols  df out[8]:    trinucleotide first second third 0                                  0           aca          c     1           acc          c     c 2           acg          c     g 3           act          c     t 4           aca          c     5           acc          c     c 6           acg          c     g 7           act          c     t 8           aca          c     9           acc          c     c