df = pd.DataFrame({'A': ['x1','x2','x3', 'x4'], 'B':[['v1','v2'],['v3','v4'],['v5','v6'],['v7','v8']], 'C':[['c1','c2'],['c3','c4'],['c5','c6'],['c7','c8']],'D':[['d1','d2'],['d3','d4'],['d5','d6'],['d7','d8']], 'E':[['e1','e2'],['e3','e4'],['e5','e6'],['e7','e8']]})
    A       B          C           D           E
0   x1  [v1, v2]    [c1, c2]    [d1, d2]    [e1, e2]
1   x2  [v3, v4]    [c3, c4]    [d3, d4]    [e3, e4]
2   x3  [v5, v6]    [c5, c6]    [d5, d6]    [e5, e6]
3   x4  [v7, v8]    [c7, c8]    [d7, d8]    [e7, e8]

A       B          C           D           E
0   x1      v1         c1         d1          e1
0   x1      v2         c2         d2          e2
1   x2      v3         c3         d3          e3
1   x2      v4         c4         d4          e4
.....

def explode(df, lst_cols, fill_value=''):
    # make sure `lst_cols` is a list
    if lst_cols and not isinstance(lst_cols, list):
        lst_cols = [lst_cols]
    # all columns except `lst_cols`
    idx_cols = df.columns.difference(lst_cols)

    # calculate lengths of lists
    lens = df[lst_cols[0]].str.len()

    if (lens > 0).all():
        # ALL lists in cells aren't empty
        return pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols})
          .loc[:, df.columns]
    else:
        # at least one list in cells is empty
        return pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols})
          .append(df.loc[lens==0, idx_cols]).fillna(fill_value)
          .loc[:, df.columns]

In [82]: explode(df, lst_cols=list('BCDE'))
Out[82]:
    A   B   C   D   E
0  x1  v1  c1  d1  e1
1  x1  v2  c2  d2  e2
2  x2  v3  c3  d3  e3
3  x2  v4  c4  d4  e4
4  x3  v5  c5  d5  e5
5  x3  v6  c6  d6  e6
6  x4  v7  c7  d7  e7
7  x4  v8  c8  d8  e8

In [1253]: (df.set_index('A')
              .apply(lambda x: x.apply(pd.Series).stack())
              .reset_index()
              .drop('level_1', 1))
Out[1253]:
    A   B   C   D   E
0  x1  v1  c1  d1  e1
1  x1  v2  c2  d2  e2
2  x2  v3  c3  d3  e3
3  x2  v4  c4  d4  e4
4  x3  v5  c5  d5  e5
5  x3  v6  c6  d6  e6
6  x4  v7  c7  d7  e7
7  x4  v8  c8  d8  e8