I have a table that looks something like this:
datetime | category |
---|---|
2021.31.01 12:12:00 | X |
2021.31.01 12:23:00 | X |
2021.31.01 15:01:00 | X |
2021.31.01 15:23:00 | X |
2021.31.01 15:37:00 | X |
2021.30.02 11:23:00 | Y |
2021.30.02 15:13:00 | X |
What is needed is to get the max count value of each type grouped by date and hour.
So, the end result would look something this:
category | date_hour | number_of_occurances |
---|---|---|
X | 2021.31.01 15:00:00 | 3 |
Y | 2021.30.02 11:00:00 | 1 |
How the query looks now:
SELECT
category,
to_timestamp(datetime, 'y-M-d H') as date_hour,
COUNT(*) AS number_of_occurances
FROM <my_table>
GROUP BY category, date_hour
ORDER BY number_of_occurances DESC
Use a window function to find the top count per category and then only show the category/hours ranked #1.
SELECT category, date_hour, number_of_occurances
FROM
(
SELECT
category,
TRUNC(datetime, 'HH24') AS date_hour,
COUNT(*) AS number_of_occurances,
RANK() OVER (PARTITION BY category ORDER BY COUNT(*) DESC) AS rnk
FROM <my_table>
GROUP BY category, TRUNC(datetime, 'HH24')
) ranked
WHERE rnk = 1
ORDER BY category;