How to split/expand a string value into several pandas DataFrame rows?

Question

Let\'s say my DataFrame df is created like this:

df = pd.DataFrame({\"title\" : [\"Robin Hood\", \"Madagaskar\"],
                  \"genres\" :         


        

Answer 1

You can use np.repeat with numpy.concatenate for flattening.

splitted = df['genres'].str.split(',\s*')
l = splitted.str.len()

df1 = pd.DataFrame({'title': np.repeat(df['title'].values, l),
                     'genres':np.concatenate(splitted.values)}, columns=['title','genres'])
print (df1)
        title      genres
0  Robin Hood      Action
1  Robin Hood   Adventure
2  Madagaskar      Family
3  Madagaskar   Animation
4  Madagaskar      Comedy

Timings:

df = pd.concat([df]*100000).reset_index(drop=True)

In [95]: %%timeit
    ...: splitted = df['genres'].str.split(',\s*')
    ...: l = splitted.str.len()
    ...: 
    ...: df1 = pd.DataFrame({'title': np.repeat(df['title'].values, l),
    ...:                      'genres':np.concatenate(splitted.values)}, columns=['title','genres'])
    ...: 
    ...: 
1 loop, best of 3: 709 ms per loop

In [96]: %timeit (df.set_index('title')['genres'].str.split(',\s*', expand=True).stack().reset_index(name='genre').drop('level_1',1))
1 loop, best of 3: 750 ms per loop