How to make first three elements in a list as columns and the rest as rows - Python

Question

df = pd.DataFrame({'Categotry':['Food','Animal'],
          'Detail':[['Name','Color','Sweet?','Bread','Brown','No','Rice','White','No','Sushi','N/A','No'],
                    ['Name','Predator?','Habitat','Tigers','Yes','Forests','Lions','Yes','Savanna','Deers','No','Hardwoods']]})

I have above dataframe and I want to split the Detail column as below:

How can I do that in Python?

Thanks for the help.

Answer 1

Custom Function

def process_details(details):
    cols, *data = np.reshape(details, (-1, 3))
    return pd.DataFrame(data, columns=cols)

I use np.reshape because I'm used to it. However, this can accomplish the same thing.

def process_details(details):
    cols, *data = zip(*[iter(details)] * 3)
    return pd.DataFrame(data, columns=cols)

---

Side by Side

Because the column names don't match up

pd.concat({
    cat: process_details(details)
    for cat, details in zip(*map(df.get, df))
}, sort=False, axis=1)

   Animal                        Food              
     Name Predator?    Habitat   Name  Color Sweet?
0  Tigers       Yes    Forests  Bread  Brown     No
1   Lions       Yes    Savanna   Rice  White     No
2   Deers        No  Hardwoods  Sushi    N/A     No

But if you insist on stacking them

pd.concat({
    cat: process_details(details)
    for cat, details in zip(*map(df.get, df))
}, sort=False)

            Name Predator?    Habitat  Color Sweet?
Animal 0  Tigers       Yes    Forests    NaN    NaN
       1   Lions       Yes    Savanna    NaN    NaN
       2   Deers        No  Hardwoods    NaN    NaN
Food   0   Bread       NaN        NaN  Brown     No
       1    Rice       NaN        NaN  White     No
       2   Sushi       NaN        NaN    N/A     No