Series and DataFrame methods define a .explode() method that explodes lists into separate rows. See the docs section on Exploding a list-like column.
df = pd.DataFrame({
'var1': [['a', 'b', 'c'], ['d', 'e',], [], np.nan],
'var2': [1, 2, 3, 4]
})
df
var1 var2
0 [a, b, c] 1
1 [d, e] 2
2 [] 3
3 NaN 4
df.explode('var1')
var1 var2
0 a 1
0 b 1
0 c 1
1 d 2
1 e 2
2 NaN 3 # empty list converted to NaN
3 NaN 4 # NaN entry preserved as-is
# to reset the index to be monotonically increasing...
df.explode('var1').reset_index(drop=True)
var1 var2
0 a 1
1 b 1
2 c 1
3 d 2
4 e 2
5 NaN 3
6 NaN 4
Note that this also handles mixed columns of lists and scalars, as well as empty lists and NaNs appropriately (this is a drawback of repeat-based solutions).
However, you should note that explode only works on a single column (for now).
P.S.: if you are looking to explode a column of strings, you need to split on a separator first, then use explode. See this (very much) related answer by me.