Splitting the row into new line and adding corresponding matching value from other column

Question

I have a datafarme like following

  data = pd.DataFrame({'Name': ['CTA15;CTA16;CAR;', 'AC007;AC008;GOO7;G008;F009', 'AC09;BC09;C09;V09;B0P', 'UF09;GF09;HF09;MN08'],  
    'Sample':['JAK_1', 'TOR2', 'Gilo', 'ALR']})
data

                Name    Sample
0   CTA15;CTA16;CAR;           JAK_1
1   AC007;AC008;GOO7;G008;F009  TOR2
2   AC09;BC09;C09;V09;B0P       Gilo
3   UF09;GF09;HF09;MN08         ALR

And I need to split the column Name and into a new row and add the value in column Sample correspondingly.In the end, I am aiming to have a data frame like this,

    Name    Sample
0   CTA15   JAK_1
1   CTA16   JAK_1
2   CAR JAK_1
3   AC007   TOR2
4   AC008   TOR2
5   GOO7    TOR2
6   G008    TOR2
7   F009    TOR2
8   AC09    Gilo
9   BC09    Gilo
10  C09 Gilo
11  V09 Gilo
12  B0P Gilo
13  UF09    ALR
14  GF09    ALR
15  HF09    ALR
16  MN08    ALR

I need to split with ';' into the new line and add the value from Sample column to each correspondingly.

Answer 1

You can use str.strip for remove ; in start of end of some strings, str.split for list s, then get len for length of them.

Last create new DataFrame by constructor with numpy.repeat and numpy.concatenate :

vals = data['Name'].str.strip(';').str.split(';')
l = vals.str.len()
df = pd.DataFrame({'Sample':np.repeat(data['Sample'].values, l), 
                   'Name':np.concatenate(vals.values)})
print (df)
     Name Sample
0   CTA15  JAK_1
1   CTA16  JAK_1
2     CAR  JAK_1
3   AC007   TOR2
4   AC008   TOR2
5    GOO7   TOR2
6    G008   TOR2
7    F009   TOR2
8    AC09   Gilo
9    BC09   Gilo
10    C09   Gilo
11    V09   Gilo
12    B0P   Gilo
13   UF09    ALR
14   GF09    ALR
15   HF09    ALR
16   MN08    ALR

Alternative solution:

df = data.join(data.pop('Name')
                   .str.strip(';')
                   .str.split(';', expand=True)
                   .stack()
                   .reset_index(level=1, drop=True)
                   .rename('Name')).reset_index(drop=True)
print (df)
   Sample   Name
0   JAK_1  CTA15
1   JAK_1  CTA16
2   JAK_1    CAR
3    TOR2  AC007
4    TOR2  AC008
5    TOR2   GOO7
6    TOR2   G008
7    TOR2   F009
8    Gilo   AC09
9    Gilo   BC09
10   Gilo    C09
11   Gilo    V09
12   Gilo    B0P
13    ALR   UF09
14    ALR   GF09
15    ALR   HF09
16    ALR   MN08