python - 如何将 pandas df 变成带有子组的字典

Question

我有一个看起来像这样的数据框:

d = {'country': ['America','America','America','America','Canada','Canada','Canada','Canada'],\
     'city': ['New York','New York','San Francisco','San Francisco',u'Montréal',u'Montréal','Toronto','Toronto'],\
     'landmark': ['Statue of Liberty', 'Empire State Building','Golden Gate Bridge',\
                  'Mission District','Biodome', 'Parc Laurier', 'CN Tower', 'Royal Ontario Museum']}
pd.DataFrame(data = d)

我希望它是这样的字典:

all_options = {
    'America': {
        'New York': ['Statue of Liberty', 'Empire State Building'],
        'San Francisco': ['Golden Gate Bridge', 'Mission District'],
    },
    'Canada': {
        u'Montréal': ['Biodome', 'Parc Laurier'],
        'Toronto': ['CN Tower', 'Royal Ontario Museum'],
    }
}   

Answer 1

你可以用 dict comprehension 来做，比如:

all_options = {country: grp.groupby('city')['landmark'].apply(list).to_dict()
               for country, grp in df.groupby('country')}

[输出]

{'America': {'New York': ['Statue of Liberty', 'Empire State Building'],
  'San Francisco': ['Golden Gate Bridge', 'Mission District']},
 'Canada': {'Montréal': ['Biodome', 'Parc Laurier'],
  'Toronto': ['CN Tower', 'Royal Ontario Museum']}}

---

或者，如果您更喜欢更明确的方法，这相当于 for 循环:

all_options = {}

for country, grp in df.groupby('country'):
    all_options[country] = grp.groupby('city')['landmark'].apply(list).to_dict()

---

上面的有用链接包括，DataFrame.groupby , Series.apply和 Series.to_dict