我有一个数据框，可以对每个城市的每个价格范围的商品进行分组和计数，如下所示：
list_cities = ['city-1', 'city-2', 'city-3']
list_price_ranges = ['Budget', 'Standard', 'Luxury']
df = pd.DataFrame([['city-1','Budget',72], ['city-1','Standard',219], ['city-1','Luxury',73],
['city-2','Budget',58], ['city-2','Standard',196], ['city-2','Luxury',75],
['city-3','Budget',49], ['city-3','Standard',160], ['city-3','Luxury',46]],
columns=['city', 'price range', 'number of items'])
df
它导致：
city price range number of items
0 city-1 Budget 72
1 city-1 Standard 219
2 city-1 Luxury 73
3 city-2 Budget 58
4 city-2 Standard 196
5 city-2 Luxury 75
6 city-3 Budget 49
7 city-3 Standard 160
8 city-3 Luxury 46
现在，我想将上表转换为：
Budget Standard Luxury
city-1 72 219 73
city-2 58 196 75
city-3 49 160 46
我可以使用如下代码行做到这一点：
dict_records = df.to_dict(orient='records')
list_cities_price_ranges = []
for city in list_cities:
list_city_price_ranges = []
for price_range in list_price_ranges:
for element in dict_records:
if element['city'] == city and element['price range'] == price_range:
list_city_price_ranges.append(element['number of items'])
list_cities_price_ranges.append(list_city_price_ranges)
list_cities_price_ranges
df_cities_price_ranges = pd.DataFrame(list_cities_price_ranges, index=list_cities, columns=list_price_ranges)
df_cities_price_ranges
它工作正常。
但是，是否有任何内置的pandas / DataFrame函数/方法使代码更简单，更美观？
谢谢