Pandas concatenate strings and numpy array

I have this:

n = 5                                            
df = pandas.DataFrame(dict(j=numpy.repeat(0, n)))
df['j'] = 'prefix-'                              
df['j'] += numpy.arange(n).astype('U')           
df['j'] += '-suffix'                             
print(df)                                        

which produces:

                 j
0  prefix-0-suffix
1  prefix-1-suffix
2  prefix-2-suffix
3  prefix-3-suffix
4  prefix-4-suffix

Is there a way to do this (reasonably) in one line?

I tried:

df['j'] = 'prefix-' + numpy.arange(n).astype('U') + '-suffix'

but that resulted in this error:

numpy.core._exceptions._UFuncNoLoopError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U7'), dtype('<U21')) -> None

>Solution :

Convert as string using astype and pd.RangeIndex

# df['j'] = 'prefix-' + df['j'].astype(str) + '-suffix'
df['j'] = 'prefix-' + pd.RangeIndex(n).astype(str) + '-suffix'
print(df)

# Output
                 j
0  prefix-0-suffix
1  prefix-1-suffix
2  prefix-2-suffix
3  prefix-3-suffix
4  prefix-4-suffix