Explode column of list to multiple rows

Pandas >= 0.25

Pandas can do this in a single function call via df.explode.

df.explode('column_x')

  column_a column_b column_x
0      a_1      b_1      c_1
0      a_1      b_1      c_2
1      a_2      b_2      d_1
1      a_2      b_2      d_2

Note that you can only explode a Series/DataFrame on one column.

---

Pandas < 0.25

Call np.repeat along the 0^th axis for every column besides column_x.

df1 = pd.DataFrame(
    df.drop('column_x', 1).values.repeat(df['column_x'].str.len(), axis=0),
    columns=df.columns.difference(['column_x'])
)
df1['column_x'] = np.concatenate(df['column_x'].values)

df1

  column_a column_b column_x
0      a_1      b_1      c_1
1      a_1      b_1      c_2
2      a_2      b_2      d_1
3      a_2      b_2      d_2

You can repeat index values:

lens = df['column_x'].str.len()
a = np.repeat(df.index.values, lens)
print (a)
[0 0 1 1]

df = df.loc[a].assign(column_x=np.concatenate(df['column_x'].values)).reset_index(drop=True)
print (df)
  column_a column_b column_x
0      a_1      b_1      c_1
1      a_1      b_1      c_2
2      a_2      b_2      d_1
3      a_2      b_2      d_2