Q:

How to break up a list into individual rows

Given the following dataframe, how do I go about splitting up the Adj. list into individual rows?
Connector Pin   Connector  Pin         Adj.      Color                                    
F123      1        F123    1         [2, 6, 7]     R
          2        F123    2   [1, 3, 6, 7, 8]     O
          3        F123    3   [2, 4, 7, 8, 9]     Y
          4        F123    4  [3, 5, 8, 9, 10]    GR
          5        F123    5        [4, 9, 10]     L
          6        F123    6         [1, 2, 7]     R
          7        F123    7   [1, 2, 3, 6, 8]     B
          8        F123    8   [2, 3, 4, 7, 9]     L
          9        F123    9  [3, 4, 5, 8, 10]    GR
          10       F123   10         [4, 5, 9]     O
C137      1        C137    1            [2, 3]     R
          2        C137    2            [1, 3]     R
          3        C137    3            [1, 2]     R

A snippet of the output I am looking for is below:
Connector Pin   Connector  Pin         Adj.      Color                                    
F123      1        F123    1           2           R
          1        F123    1           6           R
          1        F123    1           7           R

The code that I thought would work is below and the error it gives me is "Merging with both multi-indexes is not implemented"
f = df.apply(lambda x: 
pd.Series(x['Adj.']),axis=1).stack().reset_index(level=1, drop=True)
f.name = 'sample'    
df.drop('Adj.' , axis=1).join(f)

A:

In my opinion there is MultiIndex same like columns Connector and Pin, so I suggest remove it by reset_index with drop=True:
df = df.reset_index(drop=True)

Then convert column with pop to DataFrame, reshape by stack, remove second level and rename to same column name:
s = (pd.DataFrame(df.pop('Adj.').values.tolist())
        .stack()
        .reset_index(level=1, drop=True)
        .rename('Adj.')
        .astype(int)
      )

So possible join to original:
df = df.join(s).reset_index(drop=True)
print (df.head(10))
  Connector  Pin Color  Adj.
0      F123    1     R     2
1      F123    1     R     6
2      F123    1     R     7
3      F123    2     O     1
4      F123    2     O     3
5      F123    2     O     6
6      F123    2     O     7
7      F123    2     O     8
8      F123    3     Y     2
9      F123    3     Y     4

Solution with MultiIndex working too, only join by default sorting final MultiIndex:
s = (pd.DataFrame(df.pop('Adj.').values.tolist(), index=df.index)
        .stack()
        .reset_index(level=2, drop=True)
        .rename('Adj.')
        .astype(int)
      )

df = df.join(s)
print (df.head(10))
                Connector  Pin Color  Adj.
Connector1 Pin2                           
C137       1         C137    1     R     2
           1         C137    1     R     3
           2         C137    2     R     1
           2         C137    2     R     3
           3         C137    3     R     1
           3         C137    3     R     2
F123       1         F123    1     R     2
           1         F123    1     R     6
           1         F123    1     R     7
           2         F123    2     O     1

