Split dataframe with all values in one row

Question

I got the following dataframe which is created dynamically but saves all the relevant values into one row:

df

+----------------+----------------+----------------+----------------+
|       1        |       2        |       3        |       4        |
+----------------+----------------+----------------+----------------+
| a1, b1, c1, d1 | a2, b2, c2, d2 | a3, b3, c3, d3 | a4, b4, c4, d4 |
+----------------+----------------+----------------+----------------+

I need to have all a_i values in one row, all b's etc (the columns are defined and constant):

+----+----+----+----+
| 1  | 2  | 3  | 4  |
+----+----+----+----+
| a1 | a2 | a3 | a4 |
| b1 | b2 | b3 | b4 |
| c1 | c2 | c3 | c4 |
| d1 | d2 | d3 | d4 |
+----+----+----+----+

Due to the circumstances that the number of different letters in df is changing from case to case I would need a dynamic solution which converts the df into the form above.

Answer 1

Update Pandas 1.3.0 explode accepts a list of column headers.

df.explode(df.columns.tolist())

Output:

    1   2   3   4
0  a1  a2  a3  a4
0  b1  b2  b3  b4
0  c1  c2  c3  c4
0  d1  d2  d3  d4

---

Given, df with this structure:

df = pd.DataFrame({1:[np.array('a1 b1 c1 d1'.split(' '))],
                  2:[np.array('a2 b2 c2 d2'.split(' '))],
                  3:[np.array('a3 b3 c3 d3'.split(' '))],
                  4:[np.array('a4 b4 c4 d4'.split(' '))]})

Input dataframe:

                  1                 2                 3                 4
0  [a1, b1, c1, d1]  [a2, b2, c2, d2]  [a3, b3, c3, d3]  [a4, b4, c4, d4]

You can use pd.Series.explode:

df.apply(pd.Series.explode)

Output:

    1   2   3   4
0  a1  a2  a3  a4
0  b1  b2  b3  b4
0  c1  c2  c3  c4
0  d1  d2  d3  d4

Answer 2

Somewhat similar to Scott Boston's answer, but much faster (apply is notoriously slow):

pd.DataFrame(df.values[0].tolist(), columns=df.columns)
#    1   2   3   4
#0  a1  b1  c1  d1
#1  a2  b2  c2  d2
#2  a3  b3  c3  d3
#3  a4  b4  c4  d4