Python字典处理
data大柳 人气:0字典求和
edge_weights = defaultdict(lambda: defaultdict(float)) for idx,node in enumerate(graph.nodes()): node2com[node] = idx #给每一个节点初始化赋值一个团id for edge in graph[node].items(): edge_weights[node][edge[0]] = edge[1]['weight'] edge_weights
运行结果:
defaultdict(<function __main__.<lambda>()>,
{'397564': defaultdict(float,
{'15.1.18010.11898': 71,
'15.1.18010.11899': 54,
'15.1.18009.11899': 75,
'15.1.18009.11898': 160}),
'15.1.18010.11898': defaultdict(float,
{'397564': 71,
'577806': 61,
'73827465': 66,
'30009791666': 62,
'30005407392': 59,
'100293225': 102,
'30012147301': 65,
'138661946': 52}),
'1085941': defaultdict(float,
{'15.1.18007.11870': 120,
'15.1.18005.11872': 55,
'15.1.18004.11872': 75,
'15.1.18006.11870': 83,
'15.1.18004.11871': 63})
})
对上述edge_weights所有的值汇入列表并求和:
sum( [weight for start in edge_weights.keys() for end, weight in edge_weights[start].items()] )
列表剔重并计数
方法1:
统计列表中的重复项出现的次数。
循环遍历出一个可迭代对象中的元素,如果字典没有该元素,那么就让该元素作为字典的键,并将该键赋值为1,如果存在就将该元素对应的值加1.
lists = ['a','a','b',5,6,7,5,'a'] count_dict = dict() for item in lists: if item in count_dict: count_dict[item] += 1 else: count_dict[item] = 1
方法2:
使用collections.defaultdict(),将default_factory设为int,代码如下:
from collections import defaultdict #s = 'mississippi' s = ['a','a','b',5,6,7,5,'a'] d = defaultdict(int) for k in s: d[k] += 1 print('\n',d)
获取字典中最大的value
a = {'a':2,'b':3,'c':5,'d':9,'e':4} print(max(a.values()))
获取字典中出现value最大的key
a = {'a':2,'b':3,'c':5,'d':9,'e':4} print(max(a,key=a.get))
运行结果:
d
字典对应元素追加
对于列表:
s = [('yellow',1),('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
统计列表字典有两种方法:
方法1:
用dict.setdefault()实现。
代码如下:
s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)] d = {} for k, v in s: d.setdefault(k,[]).append(v) a = sorted(d.items()) print(a)
运行结果:
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
方法2;
使用collections.defaultdict(),并使用list作第一个参数,可以很容易将键-值对序列转换为列表字典,
代码如下:
from collections import defaultdict s = [('yellow',1),('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)] d = defaultdict(list) for k, v in s: d[k].append(v) a = sorted(d.items()) print(a)
运行结果:
[('blue', [2, 4]), ('red', [1]), ('yellow', [1, 3])]
当字典中没有的键第一次出现时,default_factory自动为其返回一个空列表,list.append()会将值添加进新列表;再次遇到相同的键时,list.append()将其它值再添加进该列表。这种方法比使用dict.setdefault()更为便捷。
字典对应元素追加并剃重
对于列表:
s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)]
统计并剃重:
from collections import defaultdict s = [('red', 1), ('blue', 2), ('red', 3), ('blue', 4), ('red', 1), ('blue', 4)] d = defaultdict(set) for k, v in s: d[k].add(v) print('\n',d)
运行结果:
defaultdict(<class 'set'>, {'red': {1, 3}, 'blue': {2, 4}})
对字典进行过滤
创建一个新的字典,可以利用字典推导式
headerTable = {k: v for k, v in headerTable.items() if v > 2}
反转字典的方法(字典的key和value对换)
使用字典推导:
m = {'a': 1, 'b': 2, 'c': 3, 'd': 4} {v: k for k, v in m.items()}
使用压缩器:
m = {'a': 1, 'b': 2, 'c': 3, 'd': 4} m.items() #[('a', 1), ('c', 3), ('b', 2), ('d', 4)] zip(m.values(), m.keys()) #[(1, 'a'), (3, 'c'), (2, 'b'), (4, 'd')] mi = dict(zip(m.values(), m.keys()))
字典的key和value对换并把key按照value进行列表合并
对于字典:
defaultdict(int, {'2100201919459568780': 0, '2100201927433498080': 1, '2100201935997972401': 2, '2100201934073343294': 3, '2100201938073398590': 3, '2100201938426179130': 2, '2100201938057211020': 4, '2100201938030472762': 3, '2100201940356247098': 4, '2100201939150253460': 4, '2100201935737728404': 4, '2100201938984381844': 4, '2100201937770425806': 4, '2100201937563397283': 4, '2100201941426286415': 4, '2100201936062819790': 4, '2100201936279351185': 4, '2100201934074097553': 4, '2100201940543713169': 4})
进行处理:
track_merge = defaultdict(list) for i in track_label.items(): track_merge[str(i[1])].append(i[0])
输出:
defaultdict(list,
{'0': ['2100201919459568780'],
'1': ['2100201927433498080'],
'2': ['2100201935997972401', '2100201938426179130'],
'3': ['2100201934073343294',
'2100201938073398590',
'2100201938030472762'],
'4': ['2100201938057211020',
'2100201940356247098',
'2100201939150253460',
'2100201935737728404',
'2100201938984381844',
'2100201937770425806',
'2100201937563397283',
'2100201941426286415',
'2100201936062819790',
'2100201936279351185',
'2100201934074097553',
'2100201940543713169']})
合并字典
appointment = { 'soccer' : { 'day': 20, 'month': 'april' } } appointment2 = { 'gym' : { 'day': 5, 'month': 'may' } } appointment.update(appointment2) appointment
输出:
{
'gym': {'day': 5, 'month': 'may'},
'soccer': {'day': 20, 'month': 'april'}
}
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