add "all" row to pandas group by - pandas

Question

This is my code (using pandas 0.19.2)
import pandas as pd
data=StringIO("""category,region,sales
fruits,east,12
vegatables,east,3
fruits,west,5
vegatables,wst,7
""")
df = pd.read_csv(data)
print(df.groupby('category', as_index=False).agg({'sales': sum}))
This is the output:
category sales
0 fruits 17
1 vegatables 10
My question is: how do add an 'all' row so the output would look like this:
category sales
0 fruits 17
1 vegatables 10
all 27

Answer 1

You can try pivot_table and alter the new data:
new_df = df.pivot_table(columns='category',index='region', values='sales')
new_df['all'] = new_df.sum(1)
Output:
category fruits vegatables all
region
east 12 3 15
west 5 7 12
And if you want your original data:
new_df.stack().to_frame(name='Sales').reset_index()
Output:
region category Sales
0 east fruits 12
1 east vegatables 3
2 east all 15
3 west fruits 5
4 west vegatables 7
5 west all 12

Answer 2

here is what i ended up doing:
from io import StringIO
import pandas as pd
data = StringIO("""category,region,sales
fruits,east,12
vegatables,east,3
fruits,west,5
vegatables,wst,7
""")
df = pd.read_csv(data)
body=df.groupby('category', as_index=False).agg({'sales': sum})
head=df.groupby(lambda x: True, as_index=False) #advanced panda trickery
head=head.agg({'sales': sum})
head.insert(0,'category','*all*')
print(body.append(head))
basically, create another dataframe with the 'all' row and concat