如何基于Employee ID分组计算员工得分平均值的JS实现

问题背景 #

原代码仅将所有员工的得分存入数组，输出为 ["50", "50", "90", "40", "90", "90"]。现需要按employee_id分组，计算每个员工的得分平均值，最终得到如[70,45,90]的结果（分别对应Lem、Ian、Jm的平均分）。

实现思路 #

1. 按employee_id对数据分组，记录每个员工的总分和得分次数
2. 遍历分组结果，用总分除以次数得到平均分
3. 将所有平均分提取为目标数组

原生JavaScript实现 #

const test = [
  {"name": "Lem", "employee_id": "2177", "score": "50"},
  {"name": "Ian", "employee_id": "2179", "score": "50"},
  {"name": "Lem", "employee_id": "2177", "score": "90"},
  {"name": "Ian", "employee_id": "2179", "score": "40"},
  {"name": "Jm", "employee_id": "2174", "score": "90"},
  {"name": "Jm", "employee_id": "2174", "score": "90"}
];

// 按employee_id分组，存储总分和得分次数
const groupedData = {};
test.forEach(item => {
  const id = item.employee_id;
  const score = parseInt(item.score, 10); // 转换为数字，避免字符串拼接
  if (!groupedData[id]) {
    groupedData[id] = { total: 0, count: 0 };
  }
  groupedData[id].total += score;
  groupedData[id].count += 1;
});

// 计算平均分并生成目标数组
const average = Object.values(groupedData).map(data => data.total / data.count);

console.log(average); // 输出 [70, 45, 90]

jQuery兼容实现 #

如果需要沿用原代码的jQuery语法，可使用以下方式：

var test = [
  {"name": "Lem", "employee_id": "2177", "score": "50"},
  {"name": "Ian", "employee_id": "2179", "score": "50"},
  {"name": "Lem", "employee_id": "2177", "score": "90"},
  {"name": "Ian", "employee_id": "2179", "score": "40"},
  {"name": "Jm", "employee_id": "2174", "score": "90"},
  {"name": "Jm", "employee_id": "2174", "score": "90"}
];

var groupedData = {};
$.each(test, function(_, item) {
  var id = item.employee_id;
  var score = parseInt(item.score, 10); // 转换为数字是关键
  if (!groupedData[id]) {
    groupedData[id] = { total: 0, count: 0 };
  }
  groupedData[id].total += score;
  groupedData[id].count += 1;
});

// 提取平均分组成数组
var average = $.map(groupedData, function(data) {
  return data.total / data.count;
});

console.log(average); // 输出 [70, 45, 90]

关键注意点 #

• 必须将score的字符串类型转为数字：原数据中score是字符串，直接相加会导致字符串拼接（比如"50"+"90"得到"5090"），使用parseInt()或Number()转换后才能正确计算总分。
• 分组逻辑依赖employee_id作为唯一标识，确保同一员工的所有记录被归为一组。

内容的提问来源于stack exchange，提问作者Lemuel Fajarda