I need to apply a list to a pandas dataframe by column. The operation to be performed is string concatenation. Being more specific:
Inputs I have:
df = pd.DataFrame([['a', 'b', 'c'], ['d', 'e', 'f']], columns=['Col1', 'Col2', 'Col3'])
lt = ['Prod1', 'Prod2', 'Prod3']
which results in:
>>>df
Col1 Col2 Col3
0 a b c
1 d e f
>>>lt
['Prod1', 'Prod2', 'Prod3']
moreover, the length of lt will always be equal to number of columns of df.
What I would like to have is a dataframe of this sort:
res = pd.DataFrame([['Prod1a', 'Prod2b', 'Prod3c'], ['Prod1d', 'Prod2e', 'Prod3f']],
columns=['Col1', 'Col2', 'Col3'])
which gives:
>>>res
Col1 Col2 Col3
0 Prod1a Prod2b Prod3c
1 Prod1d Prod2e Prod3f
Until now, I've been able to solve the problem looping through rows and columns but I won't give up the idea that there's a more elegant way to solve it (maybe something like apply.
Does anyone has suggestions? Thanks!
You can perform broadcasted string concatenation:
lt + df
Col1 Col2 Col3
0 Prod1a Prod2b Prod3c
1 Prod1d Prod2e Prod3f
You can also use numpy's np.char.add function.
df[:] = np.char.add(lt, df.values.astype(str))
df
Col1 Col2 Col3
0 Prod1a Prod2b Prod3c
1 Prod1d Prod2e Prod3f
Thirdly, there is the list comprehension option.
df[:] = [[i + v for i, v in zip(lt, V)] for V in df.values.tolist()]
df
Col1 Col2 Col3
0 Prod1a Prod2b Prod3c
1 Prod1d Prod2e Prod3f