Not easy, one possible solution is create helper Series
:
df.loc[df.col1 == 1, 'new_col'] = pd.Series([['a', 'b']] * len(df))
print (df)
col1 col2 new_col
0 1 4 [a, b]
1 2 5 NaN
2 3 6 NaN
Another solution, if need set missing values to empty list too is use list comprehension:
#df['new_col'] = [['a', 'b'] if x == 1 else np.nan for x in df['col1']]
df['new_col'] = [['a', 'b'] if x == 1 else [] for x in df['col1']]
print (df)
col1 col2 new_col
0 1 4 [a, b]
1 2 5 []
2 3 6 []
But then you lose the vectorised functionality which goes with using NumPy arrays held in contiguous memory blocks.