按名称对数组数据进行分组

Question

我正在尝试开发一个具有专业知识的数组 'Transport'，其中包含每个扇区和分配给它们的文本。

这是我的：


    - 卫生保健
    -- 改善医疗保健的数据驱动洞察力
    -- 新颖的数据挖掘和可视化
    -- 以人为本的增强现实和虚拟现实

    - 活力
    -- 城市分析
    -- 了解消费者行为模式
    -- 优化能源系统

这就是我想要做的：


    - 专业知识（例如运输）

    -- 部门（例如数据）
    --- 文本（例如 Urban Analytics）
    --- 文本（例如了解消费者行为模式）
    --- 文本（例如以人为中心的增强现实和虚拟现实）

    -- 部门（例如工程）
    --- 文本（例如优化能源系统）
    ---正文（如高铁与系统集成创新）
    --- 文本（例如以人为中心的机器人和自主系统）
    --- 文本（例如跨长度尺度的表面工程）

    -- 部门（例如环境）
    --- 文本（例如欧洲领先的城市模拟能力）

    - 专业知识
    -- 部门
     - - 文本

这是我目前正在使用的代码，如果有人能够提供帮助，我将不胜感激。

var items = [{
    "item": {
      "id": 0,
      "sector": 'Data',
      "expertise": ["Healthcare"],
      "text": "Data-driven insights to improve healthcare"
    }
  },
  {
    "item": {
      "id": 1,
      "sector": 'Data',
      "expertise": ["Energy", "Transport", "Cities"],
      "text": "Urban Analytics"
    }
  },
  {
    "item": {
      "id": 2,
      "sector": 'Data',
      "expertise": ["Energy", "Transport", "Consumer"],
      "text": "Understanding patterns of consumer behaviour"
    }
  },
  {
    "item": {
      "id": 3,
      "sector": 'Data',
      "expertise": ["Healthcare", "Consumer"],
      "text": "Novel data mining and visualisation"
    }
  },
  {
    "item": {
      "id": 4,
      "sector": 'Data',
      "expertise": ["Healthcare", "Transport", "Consumer"],
      "text": "Human-centred augmented and virtual realities"
    }
  },
  {
    "item": {
      "id": 5,
      "sector": 'Healthcare',
      "expertise": ["Healthcare"],
      "text": "Medical technology innovation, translation and convergence"
    }
  },
  {
    "item": {
      "id": 6,
      "sector": 'Healthcare',
      "expertise": ["Healthcare"],
      "text": "Understanding cardio metabolic disease"
    }
  },
  {
    "item": {
      "id": 7,
      "sector": 'Healthcare',
      "expertise": ["Healthcare"],
      "text": "Improving early cancer diagnosis and treatment"
    }
  },
  {
    "item": {
      "id": 8,
      "sector": 'Healthcare',
      "expertise": ["Healthcare", "Pharmaceuticals"],
      "text": "Understanding life in molecular detail"
    }
  },
  {
    "item": {
      "id": 9,
      "sector": 'Healthcare',
      "expertise": ["Healthcare"],
      "text": "Evidencing treatment through clinical trials"
    }
  },
  {
    "item": {
      "id": 10,
      "sector": 'Engineering',
      "expertise": ["Energy", "Transport"],
      "text": "Optimising energy systems"
    }
  },
  {
    "item": {
      "id": 11,
      "sector": 'Engineering',
      "expertise": ["Energy"],
      "text": "Enhancing petroleum recovery"
    }
  },
  {
    "item": {
      "id": 12,
      "sector": 'Engineering',
      "expertise": ["Transport"],
      "text": "High speed rail and system integration innovation"
    }
  },
  {
    "item": {
      "id": 13,
      "sector": 'Engineering',
      "expertise": ["Healthcare", "Electronics"],
      "text": "Terahertz frequency electronic and photonic devices"
    }
  },
  {
    "item": {
      "id": 14,
      "sector": 'Engineering',
      "expertise": ["Healthcare", "Transport", "Manufacturing"],
      "text": "Human-centred robotic and autonomous systems"
    }
  },
  {
    "item": {
      "id": 15,
      "sector": 'Engineering',
      "expertise": ["Healthcare", "Energy", "Transport", "Manufacturing"],
      "text": "Surface engineering across the length scales"
    }
  },
  {
    "item": {
      "id": 16,
      "sector": 'Engineering',
      "expertise": ["Pharmaceuticals", "Manufacturing"],
      "text": "Chemical and process engineering from molecule to product"
    }
  },
  {
    "item": {
      "id": 17,
      "sector": 'Engineering',
      "expertise": ["Pharmaceuticals"],
      "text": "Bionanotechnology for disease diagnosis, treatment and prevention"
    }
  },
  {
    "item": {
      "id": 18,
      "sector": 'Engineering',
      "expertise": ["Healthcare", "Pharmaceuticals", "Electronics", "Manufacturing"],
      "text": "Engineering materials at the atomic level"
    }
  },
  {
    "item": {
      "id": 19,
      "sector": 'Environment',
      "expertise": ["Healthcare", "Environment & Food"],
      "text": "Addressing global challenges in food security"
    }
  },
  {
    "item": {
      "id": 20,
      "sector": 'Environment',
      "expertise": ["Healthcare", "Environment & Food"],
      "text": "Interdisciplinary approaches to tackling major water issues"
    }
  },
  {
    "item": {
      "id": 21,
      "sector": 'Environment',
      "expertise": ["Cities"],
      "text": "Designing cities of the future"
    }
  },
  {
    "item": {
      "id": 22,
      "sector": 'Environment',
      "expertise": ["Transport", "Cities"],
      "text": "Europe’s leading city simulation capability"
    }
  },
  {
    "item": {
      "id": 23,
      "sector": 'Environment',
      "expertise": ["Environment & Food"],
      "text": "Robust and timely climate solutions"
    }
  }
];

let expertise;
let res = items.reduce((acc, {
  item: {
    expertise,
    text
  }
}) => {
  expertise.forEach(x => acc[x] = [...(acc[x] || []), text]);
  return acc;
}, {});


Object.entries(res).forEach(([k, v]) => {
  console.log(k + "\n->" + v.join("\n->"));
});

Answer 1

您需要为扇区增加一级：

var items = [{"item": {"id": 0,"sector": 'Data',"expertise": ["Healthcare"],"text": "Data-driven insights to improve healthcare"}},{"item": {"id": 1,"sector": 'Data',"expertise": ["Energy", "Transport", "Cities"],"text": "Urban Analytics"}},{"item": {"id": 2,"sector": 'Data',"expertise": ["Energy", "Transport", "Consumer"],"text": "Understanding patterns of consumer behaviour"}},{"item": {"id": 3,"sector": 'Data',"expertise": ["Healthcare", "Consumer"],"text": "Novel data mining and visualisation"}},{"item": {"id": 4,"sector": 'Data',"expertise": ["Healthcare", "Transport", "Consumer"],"text": "Human-centred augmented and virtual realities"}},{"item": {"id": 5,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Medical technology innovation, translation and convergence"}},{"item": {"id": 6,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Understanding cardio metabolic disease"}},{"item": {"id": 7,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Improving early cancer diagnosis and treatment"}},{"item": {"id": 8,"sector": 'Healthcare',"expertise": ["Healthcare", "Pharmaceuticals"],"text": "Understanding life in molecular detail"}},{"item": {"id": 9,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Evidencing treatment through clinical trials"}},{"item": {"id": 10,"sector": 'Engineering',"expertise": ["Energy", "Transport"],"text": "Optimising energy systems"}},{"item": {"id": 11,"sector": 'Engineering',"expertise": ["Energy"],"text": "Enhancing petroleum recovery"}},{"item": {"id": 12,"sector": 'Engineering',"expertise": ["Transport"],"text": "High speed rail and system integration innovation"}},{"item": {"id": 13,"sector": 'Engineering',"expertise": ["Healthcare", "Electronics"],"text": "Terahertz frequency electronic and photonic devices"}},{"item": {"id": 14,"sector": 'Engineering',"expertise": ["Healthcare", "Transport", "Manufacturing"],"text": "Human-centred robotic and autonomous systems"}},{"item": {"id": 15,"sector": 'Engineering',"expertise": ["Healthcare", "Energy", "Transport", "Manufacturing"],"text": "Surface engineering across the length scales"}},{"item": {"id": 16,"sector": 'Engineering',"expertise": ["Pharmaceuticals", "Manufacturing"],"text": "Chemical and process engineering from molecule to product"}},{"item": {"id": 17,"sector": 'Engineering',"expertise": ["Pharmaceuticals"],"text": "Bionanotechnology for disease diagnosis, treatment and prevention"}},{"item": {"id": 18,"sector": 'Engineering',"expertise": ["Healthcare", "Pharmaceuticals", "Electronics", "Manufacturing"],"text": "Engineering materials at the atomic level"}},{"item": {"id": 19,"sector": 'Environment',"expertise": ["Healthcare", "Environment & Food"],"text": "Addressing global challenges in food security"}},{"item": {"id": 20,"sector": 'Environment',"expertise": ["Healthcare", "Environment & Food"],"text": "Interdisciplinary approaches to tackling major water issues"}},{"item": {"id": 21,"sector": 'Environment',"expertise": ["Cities"],"text": "Designing cities of the future"}},{"item": {"id": 22,"sector": 'Environment',"expertise": ["Transport", "Cities"],"text": "Europe’s leading city simulation capability"}},{"item": {"id": 23,"sector": 'Environment',"expertise": ["Environment & Food"],"text": "Robust and timely climate solutions"}}];

const res = items.reduce((acc, {item: {sector, expertise, text}}) => {
    expertise.forEach(exp => {
        acc[exp] = acc[exp] || {};
        acc[exp][sector] = [...(acc[exp][sector] || []), text];
    });
    return acc;
}, {});

Object.entries(res).forEach(([exp, sectors]) => {
    console.log("- " + exp);
    Object.entries(sectors).forEach(([sector, texts]) => {
        console.log("-- " + sector + "\n--- " + texts.join("\n--- "));
    });
});

说明

在reduce操作中，sector也是从对象中抓取的。就像原来一样，专业知识是迭代的，但现在 acc 对象变成了两级对象，而不是只有一级。第一级属性是专业知识 (exp)。如果这样的属性还不存在，它会得到一个空对象作为值：

        acc[exp] = acc[exp] || {};

接下来的行与您已有的很像：下一个属性级别由扇区组成，并且为每个扇区维护一个文本数组。

代码的第二部分应用了与您已有的相同的原理，但又多了一层。首先迭代专业知识属性。它们以对象作为值，每个对象都具有扇区属性。内部循环又很像您所拥有的：对于每个扇区，显示扇区和关联的文本值。

Answer 2

您可以尝试以下通用方法：

想法

创建一个函数（比如 A）打印：
- 项目符号，在此解决方案中-
- 正在使用密钥
- 此键值的特定格式。
同时创建一个函数（say B）来解析 returns 格式化字符串的值。
- 对于Array，它将使用Array.join
- 对于非空对象，它将使用您在上面创建的相同函数 (A)。
- 对于非空文字值，它将return value.toString()
- 对于空值，它将 return 一个空值。

函数A和B都表示lower/next级别。因此，您必须将 - 或项目符号值添加到现有的项目符号字符串中。
由于它是一个嵌套结构，您必须清理字符串（使用 string.trim() 删除多余的 \n），这样您就不会得到多个新行。
使用这些链接功能，无论深度如何，都将以必要的格式打印。

function isEmpty(value) {
  return value === null || value === undefined
}

function getValueString(v, preString) {
  preString = `\n${preString.trim()}-`;
  return Array.isArray(v) && (preString + v.join(preString)) ||
    typeof v === 'object' && nestedLevelToString(v, preString) ||
    isEmpty(v) && v.toString() ||
    '';
}

function nestedLevelToString(data, preString) {
  preString = preString || '-';
  let output = ''
  for (const key in data) {
    output += `${preString}${key}${getValueString(data[key], preString)}`;
  }
  return output;
}

var items = [{"item": {"id": 0,"sector": 'Data',"expertise": ["Healthcare"],"text": "Data-driven insights to improve healthcare"}},{"item": {"id": 1,"sector": 'Data',"expertise": ["Energy", "Transport", "Cities"],"text": "Urban Analytics"}},{"item": {"id": 2,"sector": 'Data',"expertise": ["Energy", "Transport", "Consumer"],"text": "Understanding patterns of consumer behaviour"}},{"item": {"id": 3,"sector": 'Data',"expertise": ["Healthcare", "Consumer"],"text": "Novel data mining and visualisation"}},{"item": {"id": 4,"sector": 'Data',"expertise": ["Healthcare", "Transport", "Consumer"],"text": "Human-centred augmented and virtual realities"}},{"item": {"id": 5,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Medical technology innovation, translation and convergence"}},{"item": {"id": 6,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Understanding cardio metabolic disease"}},{"item": {"id": 7,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Improving early cancer diagnosis and treatment"}},{"item": {"id": 8,"sector": 'Healthcare',"expertise": ["Healthcare", "Pharmaceuticals"],"text": "Understanding life in molecular detail"}},{"item": {"id": 9,"sector": 'Healthcare',"expertise": ["Healthcare"],"text": "Evidencing treatment through clinical trials"}},{"item": {"id": 10,"sector": 'Engineering',"expertise": ["Energy", "Transport"],"text": "Optimising energy systems"}},{"item": {"id": 11,"sector": 'Engineering',"expertise": ["Energy"],"text": "Enhancing petroleum recovery"}},{"item": {"id": 12,"sector": 'Engineering',"expertise": ["Transport"],"text": "High speed rail and system integration innovation"}},{"item": {"id": 13,"sector": 'Engineering',"expertise": ["Healthcare", "Electronics"],"text": "Terahertz frequency electronic and photonic devices"}},{"item": {"id": 14,"sector": 'Engineering',"expertise": ["Healthcare", "Transport", "Manufacturing"],"text": "Human-centred robotic and autonomous systems"}},{"item": {"id": 15,"sector": 'Engineering',"expertise": ["Healthcare", "Energy", "Transport", "Manufacturing"],"text": "Surface engineering across the length scales"}},{"item": {"id": 16,"sector": 'Engineering',"expertise": ["Pharmaceuticals", "Manufacturing"],"text": "Chemical and process engineering from molecule to product"}},{"item": {"id": 17,"sector": 'Engineering',"expertise": ["Pharmaceuticals"],"text": "Bionanotechnology for disease diagnosis, treatment and prevention"}},{"item": {"id": 18,"sector": 'Engineering',"expertise": ["Healthcare", "Pharmaceuticals", "Electronics", "Manufacturing"],"text": "Engineering materials at the atomic level"}},{"item": {"id": 19,"sector": 'Environment',"expertise": ["Healthcare", "Environment & Food"],"text": "Addressing global challenges in food security"}},{"item": {"id": 20,"sector": 'Environment',"expertise": ["Healthcare", "Environment & Food"],"text": "Interdisciplinary approaches to tackling major water issues"}},{"item": {"id": 21,"sector": 'Environment',"expertise": ["Cities"],"text": "Designing cities of the future"}},{"item": {"id": 22,"sector": 'Environment',"expertise": ["Transport", "Cities"],"text": "Europe’s leading city simulation capability"}},{"item": {"id": 23,"sector": 'Environment',"expertise": ["Environment & Food"],"text": "Robust and timely climate solutions"}}];


let expertise;
const res = {};
res['sector'] = items.reduce((acc, {
  item: {
    expertise,
    text
  }
}) => {
  expertise.forEach(x => acc[x] = [...(acc[x] || []), text]);
  return acc;
}, {});

console.log(nestedLevelToString(res));

按名称对数组数据进行分组

Group array data by name

javascript

arrays

pure-js

typescript

说明

想法