How to calculate mean a property having condition on two other properties?

Question

This is my data:

data = 
   [{ndc_description: "VIAGRA 50 MG TABLET", new_percent_change: 12.9, year: "2017"}, 
    {ndc_description: "VIAGRA 50 MG TABLET", new_percent_change: 12.9, year: "2019"}, 
    {ndc_description: "VIAGRA 50 MG TABLET", new_percent_change: 12.9, year: "2017"}, 
    {ndc_description: "JANUVIA 100 MG TABLET", new_percent_change: 4.41, year: "2017"},
    {ndc_description: "JANUVIA 100 MG TABLET", new_percent_change: 4.41, year: "2019"},
    {ndc_description: "JANUVIA 100 MG TABLET",new_percent_change: 4.41, year: "2017"}]

How can I mean the new_percent_change for each of two ndc_description and it's relative year? I want to add another column after "year" to contain calculated value.

Update: I could calculate the mean

roll = d3.rollups(data, v => d3.mean(v, d => d.new_percent_change), d => d.year, d => d.ndc_description)

but I don't know how to assign each value to the data array.

Answer 1

Since roll is an array of arrays with the means, you can do nested forEach loops to find the correct data object, tio which you will pass the mean:

roll.forEach(yearArray => {
  yearArray[1].forEach(description => {
    const foundObj = data.filter(e => e.year === yearArray[0] && e.ndc_description === description[0]);
    foundObj.forEach(obj => obj.mean = description[1])
  })
});

Here's a demo, I changed some values so you can see the correct means:

const data = [{
    ndc_description: "VIAGRA 50 MG TABLET",
    new_percent_change: 10.9,
    year: "2017"
  },
  {
    ndc_description: "VIAGRA 50 MG TABLET",
    new_percent_change: 12.3,
    year: "2019"
  },
  {
    ndc_description: "VIAGRA 50 MG TABLET",
    new_percent_change: 12.9,
    year: "2017"
  },
  {
    ndc_description: "JANUVIA 100 MG TABLET",
    new_percent_change: 8.41,
    year: "2017"
  },
  {
    ndc_description: "JANUVIA 100 MG TABLET",
    new_percent_change: 5.41,
    year: "2019"
  },
  {
    ndc_description: "JANUVIA 100 MG TABLET",
    new_percent_change: 4.41,
    year: "2017"
  }
];


const roll = d3.rollups(data, v => d3.mean(v, d => d.new_percent_change), d => d.year, d => d.ndc_description);

roll.forEach(yearArray => {
  yearArray[1].forEach(description => {
    const foundObj = data.filter(e => e.year === yearArray[0] && e.ndc_description === description[0]);
    foundObj.forEach(obj => obj.mean = description[1])
  })
});

console.log(data)

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