将数据框分组并将数据从几列聚合到一个新列中

Question

I want to group this dataframe by column a , and create a new column ( d ) with all values from both column b and column c .

data_dict = {'a': list('aabbcc'),
             'b': list('123456'),
             'c': list('xxxyyy')}

df = pd.DataFrame(data_dict)

From this...

to this

I've figured out one way of doing it,

df['d'] = df['b'] + df['c']
df.groupby('a').agg({'d': lambda x: ','.join(x)})

but is there a more pandas way ?

Answer 1

I think "more pandas" is hard to define, but you are able to groupby agg directly on the series if you're trying to avoid the temp column:

g = (df['b'] + df['c']).groupby(df['a']).agg(','.join).to_frame('d')

g :

       d
a       
a  1x,2x
b  3x,4y
c  5y,6y