Query Cities w/Enrichment

Let's triple spice it and add Zoomers, Moomers (Millenials need a trendier name), and Boomers in addition to our price feed data for one common set of analysis.

Key Notes

We layer on census underneath the cities breakouts
Add Census data such as Boomers_Female_Population
Include TOTAL_POPULATION to calculate percentages
Only want the most recent year of Census, order_by YEAR in desc and limit 1

query MyQuery {
  MSA(where: {MSA_NAME: {_eq: "New York-Newark-Jersey City, NY-NJ-PA"}}) {
    MSA_NAME
    parcl_price_feed_aggregate(limit: 14, order_by: {DATE: desc}) {
      aggregate {
        avg {
          PARCL_PRICE_FEED
        }
      }
    }
    cities(limit: 2, order_by: {CITY_NAME: asc}) {
      CITY_NAME
      parcl_price_feed(limit: 3, order_by: {DATE: desc}) {
        PARCL_PRICE_FEED
        DATE
      }
      census(limit: 1, order_by: {YEAR: desc}) {
        Boomers_Female_Population
        Boomers_Male_Population
        Millennial_Male_Population
        Millennial_Female
        Gen_Z_Female_Population
        Gen_Z_Male_Population
        POP_TOTAL
      }
    }
  }
}

Results

{
  "data": {
    "MSA": [
      {
        "MSA_NAME": "New York-Newark-Jersey City, NY-NJ-PA",
        "parcl_price_feed_aggregate": {
          "aggregate": {
            "avg": {
              "PARCL_PRICE_FEED": 323.92405795264
            }
          }
        },
        "cities": [
          {
            "CITY_NAME": "Airmont",
            "parcl_price_feed": [
              {
                "PARCL_PRICE_FEED": 341.3143958152173,
                "DATE": "2022-10-21"
              },
              {
                "PARCL_PRICE_FEED": 337.0259137499999,
                "DATE": "2022-10-20"
              },
              {
                "PARCL_PRICE_FEED": 336.15947946739124,
                "DATE": "2022-10-10"
              }
            ],
            "census": [
              {
                "Boomers_Female_Population": 3844,
                "Boomers_Male_Population": 3684,
                "Millennial_Male_Population": 2569,
                "Millennial_Female": 2605,
                "Gen_Z_Female_Population": 3887,
                "Gen_Z_Male_Population": 3857,
                "ESTIMATE_TOTAL_POPULATION": 34532
              }
            ]
          },
          ...
          }
          }

Results