如何按特定键的值对词典列表进行排序?鉴于:
[{'name': 'Homer', 'age': 39}, {'name': 'Bart', 'age': 10}]
按名称排序时,应为:
[{'name': 'Bart', 'age': 10}, {'name': 'Homer', 'age': 39}]
如何按特定键的值对词典列表进行排序?鉴于:
[{'name': 'Homer', 'age': 39}, {'name': 'Bart', 'age': 10}]
按名称排序时,应为:
[{'name': 'Bart', 'age': 10}, {'name': 'Homer', 'age': 39}]
当前回答
使用Pandas包是另一种方法,尽管其大规模运行时比其他人提出的更传统的方法慢得多:
import pandas as pd
listOfDicts = [{'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}]
df = pd.DataFrame(listOfDicts)
df = df.sort_values('name')
sorted_listOfDicts = df.T.to_dict().values()
下面是一个小列表和一个大(100k+)的字典列表的一些基准值:
setup_large = "listOfDicts = [];\
[listOfDicts.extend(({'name':'Homer', 'age':39}, {'name':'Bart', 'age':10})) for _ in range(50000)];\
from operator import itemgetter;import pandas as pd;\
df = pd.DataFrame(listOfDicts);"
setup_small = "listOfDicts = [];\
listOfDicts.extend(({'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}));\
from operator import itemgetter;import pandas as pd;\
df = pd.DataFrame(listOfDicts);"
method1 = "newlist = sorted(listOfDicts, key=lambda k: k['name'])"
method2 = "newlist = sorted(listOfDicts, key=itemgetter('name')) "
method3 = "df = df.sort_values('name');\
sorted_listOfDicts = df.T.to_dict().values()"
import timeit
t = timeit.Timer(method1, setup_small)
print('Small Method LC: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup_small)
print('Small Method LC2: ' + str(t.timeit(100)))
t = timeit.Timer(method3, setup_small)
print('Small Method Pandas: ' + str(t.timeit(100)))
t = timeit.Timer(method1, setup_large)
print('Large Method LC: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup_large)
print('Large Method LC2: ' + str(t.timeit(100)))
t = timeit.Timer(method3, setup_large)
print('Large Method Pandas: ' + str(t.timeit(1)))
#Small Method LC: 0.000163078308105
#Small Method LC2: 0.000134944915771
#Small Method Pandas: 0.0712950229645
#Large Method LC: 0.0321750640869
#Large Method LC2: 0.0206089019775
#Large Method Pandas: 5.81405615807
其他回答
sorted()函数接受key=参数
newlist = sorted(list_to_be_sorted, key=lambda d: d['name'])
或者,您可以使用operator.itemgetter而不是自己定义函数
from operator import itemgetter
newlist = sorted(list_to_be_sorted, key=itemgetter('name'))
为完整起见,添加reverse=True以降序排序
newlist = sorted(list_to_be_sorted, key=itemgetter('name'), reverse=True)
您必须实现自己的比较函数,该函数将通过名称键的值来比较字典。参见PythonInfo Wiki中的排序迷你如何
我一直是lambda过滤器的忠实粉丝。然而,若考虑到时间复杂性,这并不是最好的选择。
第一个选项
sorted_list = sorted(list_to_sort, key= lambda x: x['name'])
# Returns list of values
第二个选项
list_to_sort.sort(key=operator.itemgetter('name'))
# Edits the list, and does not return a new list
快速比较执行时间
# First option
python3.6 -m timeit -s "list_to_sort = [{'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}, {'name':'Faaa', 'age':57}, {'name':'Errr', 'age':20}]" -s "sorted_l=[]" "sorted_l = sorted(list_to_sort, key=lambda e: e['name'])"
1000000个循环,最好为3个:每个循环0.736µsec
# Second option
python3.6 -m timeit -s "list_to_sort = [{'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}, {'name':'Faaa', 'age':57}, {'name':'Errr', 'age':20}]" -s "sorted_l=[]" -s "import operator" "list_to_sort.sort(key=operator.itemgetter('name'))"
1000000个循环,最好为3个:每个循环0.438µsec
您可以使用以下选项:
lst = [{'name': 'Homer', 'age': 39}, {'name': 'Bart', 'age': 10}]
sorted_lst = sorted(lst, key=lambda x: x['age']) # change this to sort by a different field
print(sorted_lst)
假设我有一本字典D,其中包含以下元素。要排序,只需使用sorted中的key参数传递自定义函数,如下所示:
D = {'eggs': 3, 'ham': 1, 'spam': 2}
def get_count(tuple):
return tuple[1]
sorted(D.items(), key = get_count, reverse=True)
# Or
sorted(D.items(), key = lambda x: x[1], reverse=True) # Avoiding get_count function call
看看这个。