在python中过滤JSON数据答案

【问题标题】：Filtering JSON data in python在python中过滤JSON数据
【发布时间】：2023-03-25 13:21:02
【问题描述】：

我有一个包含 5000 个项目的电影演员阵容的 ~~CSV~~ JSON 文件。第一项看起来像这样：

[{
    "cast_id": 5,
    "character": "John Carter",
    "credit_id": "52fe479ac3a36847f813ea75",
    "gender": 2,
    "id": 60900,
    "name": "Taylor Kitsch",
    "order": 0
}, {
    "cast_id": 20,
    "character": "Dejah Thoris",
    "credit_id": "52fe479ac3a36847f813eab3",
    "gender": 1,
    "id": 21044,
    "name": "Lynn Collins",
    "order": 1
}, {
    "cast_id": 7,
    "character": "Sola",
    "credit_id": "52fe479ac3a36847f813ea79",
    "gender": 1,
    "id": 2206,
    "name": "Samantha Morton",
    "order": 2
}, {
    "cast_id": 3,
    "character": "Tars Tarkas",
    "credit_id": "52fe479ac3a36847f813ea6d",
    "gender": 2,
    "id": 5293,
    "name": "Willem Dafoe",
    "order": 3
}, {
    "cast_id": 8,
    "character": "Tal Hajus",
    "credit_id": "52fe479ac3a36847f813ea7d",
    "gender": 2,
    "id": 19159,
    "name": "Thomas Haden Church",
    "order": 4
}, {
    "cast_id": 2,
    "character": "Matai Shang",
    "credit_id": "52fe479ac3a36847f813ea69",
    "gender": 2,
    "id": 2983,
    "name": "Mark Strong",
    "order": 5
}, {
    "cast_id": 4,
    "character": "Tardos Mors",
    "credit_id": "52fe479ac3a36847f813ea71",
    "gender": 2,
    "id": 8785,
    "name": "Ciar\u00e1n Hinds",
    "order": 6
}, {
    "cast_id": 9,
    "character": "Sab Than",
    "credit_id": "52fe479ac3a36847f813ea81",
    "gender": 2,
    "id": 17287,
    "name": "Dominic West",
    "order": 7
}, {
    "cast_id": 10,
    "character": "Kantos Kan",
    "credit_id": "52fe479ac3a36847f813ea85",
    "gender": 2,
    "id": 17648,
    "name": "James Purefoy",
    "order": 8
}, {
    "cast_id": 11,
    "character": "Powell",
    "credit_id": "52fe479ac3a36847f813ea89",
    "gender": 2,
    "id": 17419,
    "name": "Bryan Cranston",
    "order": 9
}, {
    "cast_id": 12,
    "character": "Sarkoja",
    "credit_id": "52fe479ac3a36847f813ea8d",
    "gender": 1,
    "id": 6416,
    "name": "Polly Walker",
    "order": 10
}, {
    "cast_id": 13,
    "character": "Edgar Rice Burroughs",
    "credit_id": "52fe479ac3a36847f813ea91",
    "gender": 2,
    "id": 57675,
    "name": "Daryl Sabara",
    "order": 11
}, {
    "cast_id": 14,
    "character": "Stayman #1 / Helm",
    "credit_id": "52fe479ac3a36847f813ea95",
    "gender": 2,
    "id": 89830,
    "name": "Arkie Reece",
    "order": 12
}, {
    "cast_id": 15,
    "character": "Stayman #3",
    "credit_id": "52fe479ac3a36847f813ea99",
    "gender": 2,
    "id": 205278,
    "name": "Davood Ghadami",
    "order": 13
}, {
    "cast_id": 16,
    "character": "Lightmaster",
    "credit_id": "52fe479ac3a36847f813ea9d",
    "gender": 1,
    "id": 218345,
    "name": "Pippa Nixon",
    "order": 14
}, {
    "cast_id": 46,
    "character": "Thern #2",
    "credit_id": "584ef986c3a3682a940010d0",
    "gender": 2,
    "id": 1390394,
    "name": "James Embree",
    "order": 15
}, {
    "cast_id": 77,
    "character": "Thern #1",
    "credit_id": "58c68f82c3a3684114014f58",
    "gender": 0,
    "id": 1518112,
    "name": "Philip Philmar",
    "order": 16
}, {
    "cast_id": 47,
    "character": "Pretty Woman in NYC Doorway",
    "credit_id": "584f133992514107110024b8",
    "gender": 1,
    "id": 1721985,
    "name": "Emily Tierney",
    "order": 17
}, {
    "cast_id": 48,
    "character": "Telegraph Clerk",
    "credit_id": "584f16d192514107000026a2",
    "gender": 2,
    "id": 1721992,
    "name": "Edmund Kente",
    "order": 18
}, {
    "cast_id": 49,
    "character": "Dalton",
    "credit_id": "584f1a94c3a3682a8d0026e7",
    "gender": 2,
    "id": 118617,
    "name": "Nicholas Woodeson",
    "order": 19
}, {
    "cast_id": 50,
    "character": "Stable Boy",
    "credit_id": "584f1f2b9251410700002be9",
    "gender": 2,
    "id": 1722006,
    "name": "Kyle Agnew",
    "order": 20
}, {
    "cast_id": 51,
    "character": "Dix the Storekeeper",
    "credit_id": "584f28aec3a3683150000214",
    "gender": 2,
    "id": 130129,
    "name": "Don Stark",
    "order": 21
}, {
    "cast_id": 52,
    "character": "Rowdy #1",
    "credit_id": "58580465c3a3683150056d0c",
    "gender": 2,
    "id": 65716,
    "name": "Josh Daugherty",
    "order": 22
}, {
    "cast_id": 53,
    "character": "Rowdy #2",
    "credit_id": "58580cd89251411a4605f517",
    "gender": 2,
    "id": 1724736,
    "name": "Jared Cyr",
    "order": 23
}, {
    "cast_id": 37,
    "character": "Stockade Guard",
    "credit_id": "54e5a58d925141529c000f89",
    "gender": 2,
    "id": 62082,
    "name": "Christopher Goodman",
    "order": 24
}, {
    "cast_id": 54,
    "character": "Sarah Carter",
    "credit_id": "585823dc925141594100c816",
    "gender": 1,
    "id": 1367241,
    "name": "Amanda Clayton",
    "order": 25
}, {
    "cast_id": 170,
    "character": "Apache #1 (as Joe Billingiere)",
    "credit_id": "595ad40c9251410bfa04831e",
    "gender": 0,
    "id": 1844319,
    "name": "Joseph Billingiere",
    "order": 26
}
]

我只需要这个文件中“name”的值。例如，在这个项目中，它将是：

Taylor Kitsch, Lynn Collins, Samantha Morton, Willem Dafoe, Thomas Haden Church, Mark Strong, Ciar Hinds, Dominic West, James Purefoy, Bryan Cranston, Polly Walker等

键为“名称”的含义。

我该怎么做呢？

【问题讨论】：

这不是 CSV，是 JSON

标签： python arrays json

【解决方案1】：

您显示的是单个 JSON 数组，而不是 CSV。（文件扩展名与 Python 无关）

从每个 JSON 数组行中的对象解析名称

import json

with open("file.txt") as f:
    for line in f:
        names = (x['name'] for x in json.loads(line))
        for name in names:
            print(name)

【讨论】：

感谢您的回答！我能够得到所有的名字，但问题是它们一个接一个地在一起，这意味着我无法根据电影来区分它们。我可以根据特定电影安排它们吗？
不清楚数据的哪一部分包含有关特定电影的任何信息，但您可以先将此处的内部循环替换为 print(list(names))

【解决方案2】：

这样的事情应该可以工作。您使用 csv 库将行转换为数组以进行迭代。 ast 库会将字符串转换为您可以键入的 dict/json 对象。

import ast
import csv
names = []

with open('csvFile.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
        names.append(ast.literal_eval(row)[name])
        # or you could print(name) here.

【讨论】：

您是否尝试使用包含问题中提供的行的 CSV 文件？

【解决方案3】：

根据您提供的内容，这是一个非常基本的示例：

>>> movie =  [{"cast_id": 5, "character": "John Carter", "credit_id": "52fe479ac3a36847f813ea75", "gender": 2, "id": 60900, "name": "Taylor Kitsch", "order": 0}, {"cast_id": 20, "character": "Dejah Thoris", "credit_id": "52fe479ac3a36847f813eab3", "gender": 1, "id": 21044, "name": "Lynn Collins", "order": 1}]
>>> for i in movie:
...     print(i["name"])
...
Taylor Kitsch
Lynn Collins

基本上，这会遍历列表中的不同字典，然后提取与 "name" 键关联的值。

需要更多信息才能对整个 csv 文件执行此操作，但这可能会帮助您入门。

【讨论】：

我在一个 excel 文件中有 5000 行这样的行。我怎样才能获得所有这 5000 行的演员姓名？
你把csv文件读入python了吗？如果您还没有，我鼓励您查看csv module for python；更具体地说是 csv.reader 和 csv.DictReader 类。
我只是放弃了 OP 提供的内容。我没有足够的业力来评论 OP 以进行澄清......但你是对的，现在看它是 JSON 文件，而不是 CSV。
我有一个包含多列的 csv 文件，我从中提取了单列演员表。此列有 5000 行 JSON 格式

【解决方案4】：

您可以直接使用过滤器提出请求

{'$filter': ['name eq Lynn Collins']}

【讨论】：

【解决方案5】：

my_list = [{
    "cast_id": 5,
    "character": "John Carter",
    "credit_id": "52fe479ac3a36847f813ea75",
    "gender": 2,
    "id": 60900,
    "name": "Taylor Kitsch",
    "order": 0
}, {
    "cast_id": 20,
    "character": "Dejah Thoris",
    "credit_id": "52fe479ac3a36847f813eab3",
    "gender": 1,
    "id": 21044,
    "name": "Lynn Collins",
    "order": 1
}, {
    "cast_id": 7,
    "character": "Sola",
    "credit_id": "52fe479ac3a36847f813ea79",
    "gender": 1,
    "id": 2206,
    "name": "Samantha Morton",
    "order": 2
}, {
    "cast_id": 3,
    "character": "Tars Tarkas",
    "credit_id": "52fe479ac3a36847f813ea6d",
    "gender": 2,
    "id": 5293,
    "name": "Willem Dafoe",
    "order": 3
}, {
    "cast_id": 8,
    "character": "Tal Hajus",
    "credit_id": "52fe479ac3a36847f813ea7d",
    "gender": 2,
    "id": 19159,
    "name": "Thomas Haden Church",
    "order": 4
}, {
    "cast_id": 2,
    "character": "Matai Shang",
    "credit_id": "52fe479ac3a36847f813ea69",
    "gender": 2,
    "id": 2983,
    "name": "Mark Strong",
    "order": 5
}, {
    "cast_id": 4,
    "character": "Tardos Mors",
    "credit_id": "52fe479ac3a36847f813ea71",
    "gender": 2,
    "id": 8785,
    "name": "Ciar\u00e1n Hinds",
    "order": 6
}, {
    "cast_id": 9,
    "character": "Sab Than",
    "credit_id": "52fe479ac3a36847f813ea81",
    "gender": 2,
    "id": 17287,
    "name": "Dominic West",
    "order": 7
}, {
    "cast_id": 10,
    "character": "Kantos Kan",
    "credit_id": "52fe479ac3a36847f813ea85",
    "gender": 2,
    "id": 17648,
    "name": "James Purefoy",
    "order": 8
}, {
    "cast_id": 11,
    "character": "Powell",
    "credit_id": "52fe479ac3a36847f813ea89",
    "gender": 2,
    "id": 17419,
    "name": "Bryan Cranston",
    "order": 9
}, {
    "cast_id": 12,
    "character": "Sarkoja",
    "credit_id": "52fe479ac3a36847f813ea8d",
    "gender": 1,
    "id": 6416,
    "name": "Polly Walker",
    "order": 10
}, {
    "cast_id": 13,
    "character": "Edgar Rice Burroughs",
    "credit_id": "52fe479ac3a36847f813ea91",
    "gender": 2,
    "id": 57675,
    "name": "Daryl Sabara",
    "order": 11
}, {
    "cast_id": 14,
    "character": "Stayman #1 / Helm",
    "credit_id": "52fe479ac3a36847f813ea95",
    "gender": 2,
    "id": 89830,
    "name": "Arkie Reece",
    "order": 12
}, {
    "cast_id": 15,
    "character": "Stayman #3",
    "credit_id": "52fe479ac3a36847f813ea99",
    "gender": 2,
    "id": 205278,
    "name": "Davood Ghadami",
    "order": 13
}, {
    "cast_id": 16,
    "character": "Lightmaster",
    "credit_id": "52fe479ac3a36847f813ea9d",
    "gender": 1,
    "id": 218345,
    "name": "Pippa Nixon",
    "order": 14
}, {
    "cast_id": 46,
    "character": "Thern #2",
    "credit_id": "584ef986c3a3682a940010d0",
    "gender": 2,
    "id": 1390394,
    "name": "James Embree",
    "order": 15
}, {
    "cast_id": 77,
    "character": "Thern #1",
    "credit_id": "58c68f82c3a3684114014f58",
    "gender": 0,
    "id": 1518112,
    "name": "Philip Philmar",
    "order": 16
}, {
    "cast_id": 47,
    "character": "Pretty Woman in NYC Doorway",
    "credit_id": "584f133992514107110024b8",
    "gender": 1,
    "id": 1721985,
    "name": "Emily Tierney",
    "order": 17
}, {
    "cast_id": 48,
    "character": "Telegraph Clerk",
    "credit_id": "584f16d192514107000026a2",
    "gender": 2,
    "id": 1721992,
    "name": "Edmund Kente",
    "order": 18
}, {
    "cast_id": 49,
    "character": "Dalton",
    "credit_id": "584f1a94c3a3682a8d0026e7",
    "gender": 2,
    "id": 118617,
    "name": "Nicholas Woodeson",
    "order": 19
}, {
    "cast_id": 50,
    "character": "Stable Boy",
    "credit_id": "584f1f2b9251410700002be9",
    "gender": 2,
    "id": 1722006,
    "name": "Kyle Agnew",
    "order": 20
}, {
    "cast_id": 51,
    "character": "Dix the Storekeeper",
    "credit_id": "584f28aec3a3683150000214",
    "gender": 2,
    "id": 130129,
    "name": "Don Stark",
    "order": 21
}, {
    "cast_id": 52,
    "character": "Rowdy #1",
    "credit_id": "58580465c3a3683150056d0c",
    "gender": 2,
    "id": 65716,
    "name": "Josh Daugherty",
    "order": 22
}, {
    "cast_id": 53,
    "character": "Rowdy #2",
    "credit_id": "58580cd89251411a4605f517",
    "gender": 2,
    "id": 1724736,
    "name": "Jared Cyr",
    "order": 23
}, {
    "cast_id": 37,
    "character": "Stockade Guard",
    "credit_id": "54e5a58d925141529c000f89",
    "gender": 2,
    "id": 62082,
    "name": "Christopher Goodman",
    "order": 24
}, {
    "cast_id": 54,
    "character": "Sarah Carter",
    "credit_id": "585823dc925141594100c816",
    "gender": 1,
    "id": 1367241,
    "name": "Amanda Clayton",
    "order": 25
}, {
    "cast_id": 170,
    "character": "Apache #1 (as Joe Billingiere)",
    "credit_id": "595ad40c9251410bfa04831e",
    "gender": 0,
    "id": 1844319,
    "name": "Joseph Billingiere",
    "order": 26
}
]

my_names = [temp_dict['name'] for temp_dict in my_list]

【讨论】：