A success story:Blue Sky Analytics

SELECT
  name,
  -- Aggregates all the points in one district
  json_agg(json_build_object('datetime', datetime, 'u_wind', u_wind, 'v_wind', v_wind, 'albedo', albedo, 'aod469', aod469, 'aod550',
FROM (
  -- Selects all the districts in Punjab
  SELECT
    name,
    shape
  FROM
    "shapes"
  WHERE
    TYPE = 'District'
    -- Selects all the `Districts` in `Punjab` state
    AND ST_WITHIN(shape, (
      SELECT
        shape FROM "shapes"
      WHERE
        name = 'Punjab'))) AS Districts
  LEFT JOIN (
    -- Select all the points in last week with daily average and within Punjab
    SELECT
    time_bucket_gapfill ('1 day', recorded_at, NOW() - interval '1 week', NOW()) AS datetime, grid, avg(u_wind) AS u_wind, avg(v_w
    FROM
      "measurements"
    WHERE
      -- Get the points within 1 week
      recorded_at < NOW()
      AND recorded_at > NOW() - interval '1 week'
      -- Get the point only in Punjab
      AND ST_WITHIN(grid, (
        SELECT
          shape FROM "shapes"
        WHERE
          name = 'Punjab'))
    GROUP BY
      grid, datetime) AS Records
    -- Join the points based on geometry
    ON ST_Within(grid, Districts.shape)
    -- finally group them together
  GROUP BY
    name