倒排索引Python

时间：2018-11-19 14:29:55

标签： python python-3.x list dictionary

我正在尝试创建以下形式的字典： {：[，{}]} 例如： d = {条款：[数字，{数字1：数字2}]} 我尝试在内部创建字典，但是我是新手，所以我不明白这是怎么可能的。问题是我想要d的形式，并且要更新number或查找term时包含number1作为键和number2作为值的字典。 所以问题是： 是否可以创建像d这样的字典？如果是这样，我该如何访问术语，数字和内部字典？

2 个答案:

答案 0 :(得分：1)

当然，只要定义就可以了：

d = {'term': [5, {6: 7}]}

由于词典只有一个键，因此您可以通过以下方式访问该键：

key = next(iter(d))

然后，您可以通过以下两种方式访问​​值5：

number = d[key][0]
number = next(iter(d.values()))[0]

类似地，您可以通过以下任一方式访问内部字典：

inner_dict = d[key][1]
inner_dict = next(iter(d.values()))[1]

如果要访问其键/值，请对inner_dict重复该过程。

答案 1 :(得分：1)

df <- structure(list(Country = c("AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB"), OfferPrice = c(0.25, 0.55, 
0.065, 0.075, 0.019, 0.0114, 0.18, 0.015, 2.8, 3.62, 0.025, 0.07, 
0.6, 0.9, 0.12, 2.72, 0.015, 0.015, 0.32, 0.2, 0.063, 0.01, 1.42, 
0.0045, 0.02, 1.15, 0.2, 17.05, 0.009, 1.8, 3.22, 0.135, 0.35, 
5, 0.37, 0.023, 0.014, 0.023, 0.35, 1.25, 0.05, 0.059, 0.2, 0.025, 
5.45, 0.05, 0.3, 0.22, 0.04, 0.035, 2, 0.32, 0.2, 0.2, 0.02, 
0.34, 0.04, 0.025, 0.03, 0.0125, 1.6, 0.03, 0.15, 13.5, 0.1, 
0.3, 0.13, 0.115, 0.35, 0.2, 0.6, 0.7, 8, 14, 25, 15.75, 3.8, 
2, 0.5, 35.2, 1.75, 0.12, 0.48, 0.15, 0.7, 0.075, 0.15, 14.5, 
0.29, 0.58, 1.75, 9, 11.5, 0.5, 0.075, 0.12, 1.1, 0.6, 0.75, 
0.26, 0.2, 0.12, 0.49, 12, 6.85, 0.55, 0.25, 1.6, 0.36, 0.06, 
2, 0.272, 41, 0.15, 1.1, 4.1, 0.6, 0.08, 1.4, 3, 0.09, 0.15, 
0.2, 0.3, 0.8, 0.21, 0.1, 0.05, 0.17, 0.1, 0.15, 0.05, 0.3, 0.6, 
0.2, 0.5, 3.45, 3, 0.07, 0.1, 0.3, 7.2, 0.4, 0.1, 12.5, 0.07, 
0.375, 0.25, 0.3, 1.15, 0.2, 3, 1, 0.3, 0.25, 530, 262, 20, 37.5, 
3422, 295, 100, 0.085, 1925, 0.3, 107.5, 10, 2.1, 3, 15, 300, 
690, 50, 410, 100, 120, 225, 40, 100, 100, 51, 10, 82, 9.58, 
269, 0.5, 271, 100, 108, 0.3, 4.5, 0.5, 0.55, 50, 0.95, 275, 
100, 170, 0.7), OfferTo1stOpen = c(18, -2.727274895, 9.230772972, 
6.666662216, -15.78947067, 5.263155937, -2.777781725, 13.33333588, 
5.000001907, -3.591157198, -0.000001490116119, 1.428570986, -4.166670322, 
0.00000264909545, -34.16666412, -0.000001051846652, 26.66666985, 
26.66666985, 9.375002861, 2.499998569, 6.34920454, 0.000002235174179, 
-0.7042223215, -11.11110687, 15.00000286, 1.304349899, -0.000001490116119, 
6.217013359, 11.11111546, 25.00000381, 0.9316761494, -0.000003973642833, 
-15.71428394, 17.20000076, -0.000001288749104, 4.347826004, 14.28571033, 
13.04347801, 4.285716057, 43.20000076, 1.99999845, 10.16949081, 
2.499998569, -4.000001431, -0.1834827513, 11.99999809, -1.666670561, 
95.45454407, -12.49999809, 25.7142849, -0.5, 18.75000191, -0.000001490116119, 
-17.50000191, -9.999998093, 44.11764526, 15.00000286, 19.99999809, 
0.000002235174179, 35.99999619, 10.62499809, 76.66667175, 6.666662216, 
-0.3703703582, -10.00000095, -100, 146.1538544, 65.21739197, 
-11.42856979, 14.99999809, -5.000003815, -11.42856979, 1.625, 
6.785714149, NA, 3.492063522, -3.684209347, -2.5, 10, -1.420456648, 
1.142857194, -12.49999809, -1.041664481, -0.000003973642833, 
-14.2857132, 39.99999619, 36.66666031, -0.3448275924, -15.51723862, 
-12.06896305, -18.2857151, 0.555555582, -5.434782505, 590, -6.666670322, 
0.000002235174179, 1.818179607, 36.66666031, -6.666666508, 0.000003667978262, 
-10.00000095, 20.83333588, -20.40816498, -2.916666746, -29.1970787, 
-0.000002167441608, -10, -18.80635834, -100, 8.333335876, -3.5, 
10.29411125, 2.097560883, -6.666670322, 7.272725105, 0.7317096591, 
19.99999619, 81.25000763, 45.00000381, -20, -11.1111145, -0.000003973642833, 
-7.500001431, -0.000003973642833, -1.250001431, -14.28571129, 
49.99999619, -10.00000095, -5.882353783, NA, 23.33332825, 19.99999809, 
18.33332825, -13.33333683, 34.99999619, -34, -19.71014595, -32.33333206, 
-21.4285717, -20.00000191, -100, 0.1388915479, 7.499998569, -20.00000191, 
-0.2399999946, 257.1428528, -16, 54, NA, -4.347824097, -100, 
6, 1, 4.999995708, -8, 8.301886559, 3.511450291, 25, 16, -1.461133838, 
-1.694915295, 1, 17.64705849, 3.376623392, 24.99999428, 3.255813837, 
34, 0.00000454130668, -3.333333254, 10.33333302, 1.666666627, 
16.231884, 9, 1.829268336, 3, 11.66666698, 4.888888836, 14.25, 
3.5, 3.5, -4.411764622, 0.200000003, 1.829268336, 53.96659851, 
9.665427208, 5, -1.586715817, 2, 1.111111164, 4.999995708, -10, 
5, -4.545456409, NA, 7.894738197, 5.454545498, 1, 11.17647076, 
25.00000191), OfferTo1stClose = c(8, -7.272729397, 9.230772972, 
7.999995708, -21.05262947, -3.508773565, -2.777781725, 0.000002235174179, 
3.571430445, -3.867400169, -0.000001490116119, 1.428570986, -6.666670322, 
-1.666664004, -35.83333206, -3.308824539, 13.33333588, 26.66666985, 
10.93750286, -0.000001490116119, 6.34920454, -9.999998093, -0.3521096706, 
11.11111546, 5.000002384, -0.4347805381, -2.500001431, 3.519066334, 
11.11111546, 27.22222519, 4.34782505, -7.407411098, -17.1428566, 
15.39999962, 4.05405283, -0.0000001943629684, 7.142853737, 13.04347801, 
2.857144594, 43.20000076, 3.999998569, 10.16949081, -7.500001431, 
3.999998569, -0.5504552126, 19.99999809, -1.666670561, 170.4545441, 
-14.99999809, 31.4285717, -0.5, 18.75000191, -20.00000191, -17.50000191, 
0.000002235174179, 44.11764526, 12.50000286, 15.99999809, 3.333335638, 
35.99999619, 10.62499809, 123.3333359, 13.3333292, -1.481481433, 
-10.00000095, -100, 138.4615479, 47.82608414, -12.85714149, 32.49999619, 
-13.33333683, -24.2857132, 1.75, -0.3571428657, NA, 3.93650794, 
-7.894735813, -7, 20, -0.9375021458, 1.714285731, -8.333331108, 
-1.041664481, 3.333329201, -19.99999809, 33.33332825, 33.33332825, 
-0.06896551698, -16.3793087, -16.3793087, -18.2857151, 2.666666746, 
2.173913002, 590, -6.666670322, -16.66666412, 2.727270603, 44.99999237, 
-10.66666698, 1.923080683, -12.50000095, 16.66666985, -22.44898033, 
-4.166666508, -39.85401535, -3.636365652, -12, -16.8959198, -100, 
0.000002235174179, -3.5, 13.97058201, 2.707317114, -8.066670418, 
5.454543114, 0.4878072143, 19.99999619, 87.50000763, 45.7142868, 
-25.66666603, -5.555559158, 16.66666222, -2.500001431, 3.333329201, 
-0.000001490116119, -14.28571129, 49.99999619, -10.00000095, 
-5.882353783, NA, 39.99999619, 19.99999809, 13.3333292, -10.00000381, 
65, -26, -19.71014595, -31.66666603, -21.4285717, -20.00000191, 
-100, -0.1388862431, 11.24999809, -20.00000191, -1.679999948, 
228.5714264, -22.66666603, 42, NA, -7.826085091, -100, 6.666666508, 
0, 4.999995708, -8, 8.301886559, 3.969465733, 26, 16, -5.084745884, 
1.322033882, 1.5, 17.64705849, 2.077922106, 24.99999428, 3.255813837, 
43, 0.00000454130668, -4.166666508, 10.33333302, 1.333333373, 
18.69565201, 9, 1.829268336, 3, 11.66666698, 3.111111164, 15, 
3.5, 3.5, -4.411764622, 0.6000000238, 50.60975647, 53.96659851, 
37.54646683, 0, -0.1476014704, 3, 1.296296239, 4.999995708, -11.11111069, 
5, -0.000002167441608, NA, 7.894738197, 4.181818008, 0.5, 10.88235283, 
25.00000191)), row.names = c(NA, -199L), vars = "Country", drop = TRUE, indices = list(
    0:61, 62:154, 155:198), group_sizes = c(62L, 93L, 44L), biggest_group_size = 93L, labels = structure(list(
    Country = c("AU", "CA", "GB")), row.names = c(NA, -3L), class = "data.frame", vars = "Country", drop = TRUE, indices = list(
    0:61, 62:154, 155:198), group_sizes = c(62L, 93L, 44L), biggest_group_size = 93L, labels = structure(list(
    Country = c("AU", "CA", "GB")), row.names = c(NA, -3L), class = "data.frame", vars = "Country", drop = TRUE)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

键的值是一个列表：

d = {"term": [5, {6: 7}]}

列表的第一个元素：

d["term"]   
[5, {6: 7}]

列表的第二个元素是字典：

d["term"][0]
5

字典键“ 6”的值为7：

d["term"][1]
{6: 7}

编辑： 一些修改示例：

d["term"][1][6]
7
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