使用 lodash 格式化数据

Question

假设我有以下 json 数组：

const input = [
  { "tx_type": "215", "dos": "2019-05-02", "payer": "Cigna", "count": 23 },
  { "tx_type": "215", "dos": "2019-05-02", "payer": "SENIORCARE Plus", "count": 75 },
  { "tx_type": "217", "dos": "2019-05-02", "payer": "Aetna", "count": 2 },
  { "tx_type": "215", "dos": "2019-05-03", "payer": "Aetna", "count": 85 },
  { "tx_type": "215", "dos": "2019-05-03", "payer": "TRICARE", "count": 1 },
  { "tx_type": "215", "dos": "2019-05-03", "payer": "Aetna", "count": 5 },
  { "tx_type": "215", "dos": "2019-05-03", "payer": "Cigna", "count": 11 }
]

它来自 postgres 9.2 db，但我正在尝试将数据放入一个 dataviz 中，它希望数据看起来像：

[
  {
    "tx_type": "x215",
    "dos": [
      { "date": "2019-05-02", "SENIORCARE Plus": 75, "Cigna": 23 },
      { "date": "2019-05-03", "Aetna": 96, "TRICARE": 1, "Cigna": 11 }
    ],
  },
  {
    "tx_type": "x215",
    "dos": [
      { "date": "2019-05-02", "Aetna": 2 }
    ]
  }
]

我已经尝试使用 lodash 通过 tx_type 使用 .groupBy("tx_type") 以及 _.chain(input).nest("tx_type").groupBy("dos").value() 对对象进行分组，以及通过 tx_type 进行过滤然后尝试组/巢...

真的，我想做的就是按 tx_type 过滤并按日期对付款人和计数进行分组。

如有任何意见，我们将不胜感激。尽管我想升级到更新版本的 postgres 并不是一个真正的选择..

Answer 1

分组 tx_type 并映射组。要创建 dos 属性，映射组中的项目，按 dos 对它们进行分组，映射结果以将每一行转换为 { data, [payer]:count } 的对象，然后合并对象：

const input = [{"tx_type":"215","dos":"2019-05-02","payer":"Cigna","count":23},{"tx_type":"215","dos":"2019-05-02","payer":"SENIORCARE Plus","count":75},{"tx_type":"217","dos":"2019-05-02","payer":"Aetna","count":2},{"tx_type":"215","dos":"2019-05-03","payer":"Aetna","count":85},{"tx_type":"215","dos":"2019-05-03","payer":"TRICARE","count":1},{"tx_type":"215","dos":"2019-05-03","payer":"Aetna","count":5},{"tx_type":"215","dos":"2019-05-03","payer":"Cigna","count":11}]

const result = _(input)
  .groupBy('tx_type')
  .map((dos, tx_type) => ({
    tx_type,
    dos: _(dos)
      .groupBy('dos')
      .map((g, date) => _.merge({}, 
        ..._.map(g, ({ payer, count }) => ({ date,  [payer]: count }))
      ))
      .value()
  }))
  .value()
  
console.log(result)

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