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https://github.com/SyncrowIOT/backend.git
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updated space models to include suggested fixes, update final logic and column names
This commit is contained in:
khuss
@ -1,14 +1,11 @@
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-- CTE for device + status log + space
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-- Query Pipeline Starts Here
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WITH device_space AS (
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SELECT
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device.uuid AS device_id,
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device.created_at,
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device.space_device_uuid AS space_id,
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"device-status-log".event_time::timestamp AS event_time,
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"device-status-log".code,
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"device-status-log".value,
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"device-status-log".log
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"device-status-log".value
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FROM device
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LEFT JOIN "device-status-log"
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ON device.uuid = "device-status-log".device_id
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@ -17,198 +14,262 @@ WITH device_space AS (
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WHERE product.cat_name = 'hjjcy'
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),
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-- Getting the hourly pollutants max min avg for each space
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average_pollutants AS (
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SELECT
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event_time::date AS event_date,
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date_trunc('hour', event_time) AS event_hour,
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space_id,
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-- AVG READINGS
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AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
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AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
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AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
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AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
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AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
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AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
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AVG(CASE WHEN code = 'air_quality_index' THEN level_to_numeric(value) END) AS air_quality_index_avg,
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-- MIN READINGS
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MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
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MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
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MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
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MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
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MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
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MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
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MIN(CASE WHEN code = 'air_quality_index' THEN level_to_numeric(value) END) AS air_quality_index_min,
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-- MAX READINGS
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MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
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MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
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MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
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MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
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MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
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MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max,
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MAX(CASE WHEN code = 'air_quality_index' THEN level_to_numeric(value) END) AS air_quality_index_max
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-- PM1
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MIN(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_min,
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AVG(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_avg,
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MAX(CASE WHEN code = 'pm1' THEN value::numeric END) AS pm1_max,
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-- PM25
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MIN(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_min,
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AVG(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_avg,
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MAX(CASE WHEN code = 'pm25_value' THEN value::numeric END) AS pm25_max,
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-- PM10
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MIN(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_min,
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AVG(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_avg,
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MAX(CASE WHEN code = 'pm10' THEN value::numeric END) AS pm10_max,
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-- VOC
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MIN(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_min,
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AVG(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_avg,
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MAX(CASE WHEN code = 'voc_value' THEN value::numeric END) AS voc_max,
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-- CH2O
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MIN(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_min,
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AVG(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_avg,
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MAX(CASE WHEN code = 'ch2o_value' THEN value::numeric END) AS ch2o_max,
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-- CO2
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MIN(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_min,
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AVG(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_avg,
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MAX(CASE WHEN code = 'co2_value' THEN value::numeric END) AS co2_max
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FROM device_space
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GROUP BY space_id, event_hour
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GROUP BY space_id, event_hour, event_date
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),
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-- Fill NULLs due to missing log values
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filled_pollutants AS (
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SELECT
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*,
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-- Forward-fill nulls using LAG() over partitioned data
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COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_filled_avg,
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COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_filled_avg,
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COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_filled_avg,
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COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_filled_avg,
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COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_filled_avg,
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COALESCE(air_quality_index_avg, LAG(air_quality_index_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS aqi_filled_avg,
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COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_min_filled,
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COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_min_filled,
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COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_min_filled,
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COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_min_filled,
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COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_min_filled,
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COALESCE(air_quality_index_min, LAG(air_quality_index_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS aqi_min_filled,
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COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_max_filled,
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COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_max_filled,
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COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_max_filled,
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COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_max_filled,
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COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_max_filled,
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COALESCE(air_quality_index_max, LAG(air_quality_index_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS aqi_max_filled
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-- AVG
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COALESCE(pm25_avg, LAG(pm25_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_avg_f,
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COALESCE(pm10_avg, LAG(pm10_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_avg_f,
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COALESCE(voc_avg, LAG(voc_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_avg_f,
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COALESCE(co2_avg, LAG(co2_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_avg_f,
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COALESCE(ch2o_avg, LAG(ch2o_avg) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_avg_f,
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-- MIN
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COALESCE(pm25_min, LAG(pm25_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_min_f,
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COALESCE(pm10_min, LAG(pm10_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_min_f,
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COALESCE(voc_min, LAG(voc_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_min_f,
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COALESCE(co2_min, LAG(co2_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_min_f,
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COALESCE(ch2o_min, LAG(ch2o_min) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_min_f,
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-- MAX
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COALESCE(pm25_max, LAG(pm25_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm25_max_f,
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COALESCE(pm10_max, LAG(pm10_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS pm10_max_f,
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COALESCE(voc_max, LAG(voc_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS voc_max_f,
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COALESCE(co2_max, LAG(co2_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS co2_max_f,
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COALESCE(ch2o_max, LAG(ch2o_max) OVER (PARTITION BY space_id ORDER BY event_hour)) AS ch2o_max_f
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FROM average_pollutants
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),
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-- Calculate max, min, avg hourly AQI for each space
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hourly_results as (
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SELECT
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space_id,
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event_hour,
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--voc_filled,
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pm25_filled_avg,
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pm10_filled_avg,
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-- co2_filled,
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--ch2o_filled,
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--aqi_filled,
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pm25_max_filled,
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pm10_max_filled,
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pm25_min_filled,
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pm10_min_filled,
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air_quality_index_avg,
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GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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--calculate_aqi('voc_value', voc_filled_avg),
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--calculate_aqi('co2_value', co2_filled_avg),
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--calculate_aqi('ch2o_value', ch2o_filled_avg)
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-- Add more AQI sources as needed
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) AS hourly_avg_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_max_filled),
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calculate_aqi('pm10', pm10_max_filled)
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) AS hourly_max_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_min_filled),
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calculate_aqi('pm10', pm10_min_filled)
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) AS hourly_min_aqi,
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case
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when GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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) <= 50 then 'Good'
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when GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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) <= 100 then 'Moderate'
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when GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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) <= 150 then 'Unhealthy for Sensitive Groups'
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when GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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) <= 200 then 'Unhealthy'
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when GREATEST(
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calculate_aqi('pm25', pm25_filled_avg),
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calculate_aqi('pm10', pm10_filled_avg)
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) <= 300 then 'Very Unhealthy'
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else 'Hazardous'
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end as aqi_category
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FROM filled_pollutants
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ORDER BY space_id, event_hour
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hourly_results AS (
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SELECT
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space_id,
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event_date,
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event_hour,
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pm1_min, pm1_avg, pm1_max,
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pm25_min_f, pm25_avg_f, pm25_max_f,
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pm10_min_f, pm10_avg_f, pm10_max_f,
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voc_min_f, voc_avg_f, voc_max_f,
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co2_min_f, co2_avg_f, co2_max_f,
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ch2o_min_f, ch2o_avg_f, ch2o_max_f,
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GREATEST(
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calculate_aqi('pm25', pm25_min_f),
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calculate_aqi('pm10', pm10_min_f)
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) AS hourly_min_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_avg_f),
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calculate_aqi('pm10', pm10_avg_f)
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) AS hourly_avg_aqi,
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GREATEST(
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calculate_aqi('pm25', pm25_max_f),
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calculate_aqi('pm10', pm10_max_f)
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) AS hourly_max_aqi,
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classify_aqi(GREATEST(
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calculate_aqi('pm25', pm25_avg_f),
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calculate_aqi('pm10', pm10_avg_f)
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)) AS aqi_category,
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classify_aqi(calculate_aqi('pm25',pm25_avg_f)) as pm25_category,
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classify_aqi(calculate_aqi('pm10',pm10_avg_f)) as pm10_category,
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classify_aqi(calculate_aqi('voc',voc_avg_f)) as voc_category,
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classify_aqi(calculate_aqi('co2',co2_avg_f)) as co2_category,
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classify_aqi(calculate_aqi('ch2o',ch2o_avg_f)) as ch2o_category
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FROM filled_pollutants
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),
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-- counting how many categories/hours are there in total (in case device(s) was disconnected could be less than 24)
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daily_category_counts AS (
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SELECT
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space_id,
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date_trunc('day', event_hour) AS event_day,
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aqi_category,
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COUNT(*) AS category_count
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SELECT space_id, event_date, aqi_category AS category, 'aqi' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_day, aqi_category
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),
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GROUP BY space_id, event_date, aqi_category
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UNION ALL
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SELECT space_id, event_date, pm25_category AS category, 'pm25' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, pm25_category
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UNION ALL
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SELECT space_id, event_date, pm10_category AS category, 'pm10' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, pm10_category
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UNION ALL
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SELECT space_id, event_date, voc_category AS category, 'voc' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, voc_category
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UNION ALL
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SELECT space_id, event_date, co2_category AS category, 'co2' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, co2_category
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UNION ALL
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SELECT space_id, event_date, ch2o_category AS category, 'ch2o' AS pollutant, COUNT(*) AS category_count
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FROM hourly_results
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GROUP BY space_id, event_date, ch2o_category
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),
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-- Aggregate Total Counts per Day
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daily_totals AS (
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SELECT
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space_id,
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event_day,
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event_date,
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SUM(category_count) AS total_count
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FROM daily_category_counts
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GROUP BY space_id, event_day
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),
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-- Calculate the daily of the daily min max avg AQI values
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daily_averages AS (
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SELECT
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space_id,
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date_trunc('day', event_hour) AS event_day,
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ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
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ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
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ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi
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FROM hourly_results
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GROUP BY space_id, event_day
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where pollutant = 'aqi'
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GROUP BY space_id, event_date
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),
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-- Pivot Categories into Columns
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daily_percentages AS (
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SELECT
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select
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dt.space_id,
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dt.event_day,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Good' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Moderate' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Unhealthy for Sensitive Groups' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Unhealthy' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Very Unhealthy' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.aqi_category = 'Hazardous' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_percentage
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dt.event_date,
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-- AQI CATEGORIES
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_aqi_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'aqi' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_aqi_percentage,
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-- PM25 CATEGORIES
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm25_percentage,
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ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm25_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm25' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm25_percentage,
|
||||
-- PM10 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_pm10_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'pm10' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_pm10_percentage,
|
||||
-- VOC CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_voc_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'voc' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_voc_percentage,
|
||||
-- CO2 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_co2_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'co2' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_co2_percentage,
|
||||
-- CH20 CATEGORIES
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Good' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS good_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Moderate' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS moderate_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy for Sensitive Groups' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_sensitive_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Very Unhealthy' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS very_unhealthy_ch2o_percentage,
|
||||
ROUND(COALESCE(SUM(CASE WHEN dcc.category = 'Hazardous' and dcc.pollutant = 'ch2o' THEN dcc.category_count ELSE 0 END) * 100.0 / dt.total_count, 0), 2) AS hazardous_ch2o_percentage
|
||||
FROM daily_totals dt
|
||||
LEFT JOIN daily_category_counts dcc
|
||||
ON dt.space_id = dcc.space_id AND dt.event_day = dcc.event_day
|
||||
GROUP BY dt.space_id, dt.event_day, dt.total_count
|
||||
)
|
||||
ON dt.space_id = dcc.space_id AND dt.event_date = dcc.event_date
|
||||
GROUP BY dt.space_id, dt.event_date, dt.total_count
|
||||
),
|
||||
|
||||
-- Final Output
|
||||
daily_averages AS (
|
||||
SELECT
|
||||
space_id,
|
||||
event_date,
|
||||
-- AQI
|
||||
ROUND(AVG(hourly_min_aqi)::numeric, 2) AS daily_min_aqi,
|
||||
ROUND(AVG(hourly_avg_aqi)::numeric, 2) AS daily_avg_aqi,
|
||||
ROUND(AVG(hourly_max_aqi)::numeric, 2) AS daily_max_aqi,
|
||||
-- PM25
|
||||
ROUND(AVG(pm25_min_f)::numeric, 2) AS daily_min_pm25,
|
||||
ROUND(AVG(pm25_avg_f)::numeric, 2) AS daily_avg_pm25,
|
||||
ROUND(AVG(pm25_max_f)::numeric, 2) AS daily_max_pm25,
|
||||
-- PM10
|
||||
ROUND(AVG(pm10_min_f)::numeric, 2) AS daily_min_pm10,
|
||||
ROUND(AVG(pm10_avg_f)::numeric, 2) AS daily_avg_pm10,
|
||||
ROUND(AVG(pm10_max_f)::numeric, 2) AS daily_max_pm10,
|
||||
-- VOC
|
||||
ROUND(AVG(voc_min_f)::numeric, 2) AS daily_min_voc,
|
||||
ROUND(AVG(voc_avg_f)::numeric, 2) AS daily_avg_voc,
|
||||
ROUND(AVG(voc_max_f)::numeric, 2) AS daily_max_voc,
|
||||
-- CO2
|
||||
ROUND(AVG(co2_min_f)::numeric, 2) AS daily_min_co2,
|
||||
ROUND(AVG(co2_avg_f)::numeric, 2) AS daily_avg_co2,
|
||||
ROUND(AVG(co2_max_f)::numeric, 2) AS daily_max_co2,
|
||||
-- CH2O
|
||||
ROUND(AVG(ch2o_min_f)::numeric, 2) AS daily_min_ch2o,
|
||||
ROUND(AVG(ch2o_avg_f)::numeric, 2) AS daily_avg_ch2o,
|
||||
ROUND(AVG(ch2o_max_f)::numeric, 2) AS daily_max_ch2o
|
||||
|
||||
FROM hourly_results
|
||||
GROUP BY space_id, event_date
|
||||
)
|
||||
SELECT
|
||||
p.space_id,
|
||||
p.event_day,
|
||||
p.good_percentage,
|
||||
p.moderate_percentage,
|
||||
p.unhealthy_sensitive_percentage,
|
||||
p.unhealthy_percentage,
|
||||
p.very_unhealthy_percentage,
|
||||
p.hazardous_percentage,
|
||||
a.daily_avg_aqi,
|
||||
a.daily_max_aqi,
|
||||
a.daily_min_aqi
|
||||
p.event_date,
|
||||
p.good_aqi_percentage, p.moderate_aqi_percentage, p.unhealthy_sensitive_aqi_percentage, p.unhealthy_aqi_percentage, p.very_unhealthy_aqi_percentage, p.hazardous_aqi_percentage,
|
||||
a.daily_avg_aqi,a.daily_max_aqi, a.daily_min_aqi,
|
||||
p.good_pm25_percentage, p.moderate_pm25_percentage, p.unhealthy_sensitive_pm25_percentage, p.unhealthy_pm25_percentage, p.very_unhealthy_pm25_percentage, p.hazardous_pm25_percentage,
|
||||
a.daily_avg_pm25,a.daily_max_pm25, a.daily_min_pm25,
|
||||
p.good_pm10_percentage, p.moderate_pm10_percentage, p.unhealthy_sensitive_pm10_percentage, p.unhealthy_pm10_percentage, p.very_unhealthy_pm10_percentage, p.hazardous_pm10_percentage,
|
||||
a.daily_avg_pm10, a.daily_max_pm10, a.daily_min_pm10,
|
||||
p.good_voc_percentage, p.moderate_voc_percentage, p.unhealthy_sensitive_voc_percentage, p.unhealthy_voc_percentage, p.very_unhealthy_voc_percentage, p.hazardous_voc_percentage,
|
||||
a.daily_avg_voc, a.daily_max_voc, a.daily_min_voc,
|
||||
p.good_co2_percentage, p.moderate_co2_percentage, p.unhealthy_sensitive_co2_percentage, p.unhealthy_co2_percentage, p.very_unhealthy_co2_percentage, p.hazardous_co2_percentage,
|
||||
a.daily_avg_co2,a.daily_max_co2, a.daily_min_co2,
|
||||
p.good_ch2o_percentage, p.moderate_ch2o_percentage, p.unhealthy_sensitive_ch2o_percentage, p.unhealthy_ch2o_percentage, p.very_unhealthy_ch2o_percentage, p.hazardous_ch2o_percentage,
|
||||
a.daily_avg_ch2o,a.daily_max_ch2o, a.daily_min_ch2o
|
||||
FROM daily_percentages p
|
||||
LEFT JOIN daily_averages a
|
||||
ON p.space_id = a.space_id AND p.event_day = a.event_day
|
||||
ORDER BY p.space_id, p.event_day;
|
||||
ON p.space_id = a.space_id AND p.event_date = a.event_date
|
||||
ORDER BY p.space_id, p.event_date;
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user