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


What’s Next