How to multipy values splited from str in DataFrame, Python?

For example DataFrame:

import pandas as pd

df = pd.DataFrame.from_dict({
    'art1':['n1','n2'],
    'sizes':['35 36 37', '36 38']
    })

print (df)

# need that

df_result = pd.DataFrame.from_dict({
    'art1':['n1','n1','n1','n2','n2'],
    'sizes':[35,36,37,36,38]
})
        
print (df_result)

BELOW IS CORRECT BUT NOT EFFICIENT DECISION !!!

lst_art = []
lst_sizes = [x.split() for x in df['sizes']]
for i in range(len(lst_sizes)):
    for j in range(len(lst_sizes[i])):
        lst_art.append(df['art1'][i])

lst_sizes = sum(lst_sizes, [])
df = pd.DataFrame({'art1':lst_art, 'sizes':lst_sizes})

print (df)

any pandas efficient way to get df_result from df?

>Solution :

You can first split the string column into a list and then you can explode each item in the list into a new row

df = pd.DataFrame.from_dict({
    'art1':['n1','n2'],
    'sizes':['35 36 37', '36 38']
    })

# convert str to list
df['sizes'] = df['sizes'].str.split()

# create one new row per item in list of `sizes`
df_result = df.explode('sizes')

or you can do an overly powerful one liner

df.assign(sizes=df['sizes'].str.split()).explode('sizes')