I have this query to show a list of trending (most searched) names on my website:
SELECT name, COUNT(*) AS total_trends
FROM trending_names
WHERE dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' // -7 days to Now()
GROUP BY name
ORDER BY COUNT(*) DESC
LIMIT 10;
...and this is the kind of results I'm printing to screen:
(numbers represent quantity of searches made)
Angelina Jolie 31,293
Rihanna 26,722
Lindsay Lohan 18,351
Brad Pitt 11,901
I would now like to change the numbers to percentages; so I really need to be getting the total count of all trending names within the last 7 days, to calculate the correct percentage.
Is there a way I can add a total count to this query, without adding an additional query?
You can do in single query :
Try Below :
SELECT name, COUNT(*) AS total_trends,
sum(if(dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' ,1,0)) as total_last_7_days,
((sum(if(dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' ,1,0)) /COUNT(*) ) *100)
as percentage // if you want to get only percentage
FROM trending_names
GROUP BY name
ORDER BY COUNT(*) DESC
LIMIT 10;
You can use a subquery :
SELECT name, ((COUNT(*)*100)/(SELECT COUNT(*) FROM trending_names)) AS total_trends
FROM trending_names
WHERE dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' // -7 days to Now()
GROUP BY name
ORDER BY COUNT(*) DESC
LIMIT 10;
I know you aren't running SQL Server, but some readers might be interested to see this compact solution that's possible (SQL Server 2008 or later). I'm not sure many people know you can have a windowed aggregate that aggregates an aggregate.
select
name,
100.0*count(*)/sum(count(*)) over () as pct_trends
from trending_names
where dateTime between getdate()-7 and getdate()
group by name;
No, I don't think so. You do need to compute that total count on a separate (sub)select
SELECT name,(total_trends*100.0/sum_total_trends) pct_trends
FROM
(
SELECT name, COUNT(*) AS total_trends
FROM trending_names
WHERE dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' // -7 days to Now()
GROUP BY name
WITH ROLLUP
) A,
(
SELECT COUNT(*) AS sum_total_trends
FROM trending_names
WHERE dateTime BETWEEN '"&fromDate&"' AND '"&toDate&"' // -7 days to Now()
) B;
Related
I currently am trying to track the number of messages sent by month as well as the volume's percent change in comparison to one year prior.
Here is my current query:
Select
a.mo,
a.ye,
a.Messages,
((a.Messages - b.Messages) / b.Messages) as "% Change"
from(
select
MONTH(post_date) as mo,
count(*) as "Messages",
YEAR(post_date) as ye
from
pm_messages
WHERE
post_date > "2018-01-01 00:00:00"
group by
year(post_date),
month(post_date)
) a
left join (
select
MONTH(post_date) as mo,
YEAR(post_date) as ye,
count(*) as "Messages"
from
pm_messages
group by
year(post_date),
month(post_date)
) b on a.mo = b.mo
and a.ye -1 = b.ye
This works great, however, it places month and year in separate columns, which has been messing up the graphs I am working with. However, when I try to pull month and year into one columns as I've done in other queries from the same table, i.e. using:
SELECT DATE_FORMAT(`post_date`,'%M %Y')
My query does not work.
Does anyone know how I can combine my current query to still calculate the return from a year prior but have month and date come up as one column, as opposed to (Month | Year | Messages | % Change)
Thanks!!
you can use extract instead of separate year() and month() functions :
EXTRACT(YEAR_MONTH from post_date)
of course you have to group by this instead of year, month . for example :
select
EXTRACT(YEAR_MONTH from post_date) yearmonth,
count(*) as "Messages"
from
pm_messages
group by
EXTRACT(YEAR_MONTH from post_date)
If you have data for every month, you can use lag():
select year(post_date) as ye, month(post_date) as mo,
count(*) as Messages,
lag(count(*)) over (partition by month(post_date) order by year(post_date)) as prev_year
from pm_messages
where post_date >= '2018-01-01'
group by year(post_date), month(post_date)
I expect this query to give me the avg value from daily active users up to date and grouped by month (from Oct to December). But the result is 164K aprox when it should be 128K. Why avg is not working? Avg should be SUM of values / number of current month days up to today.
SELECT sq.month_year AS 'month_year', AVG(number)
FROM
(
SELECT CONCAT(MONTHNAME(date), "-", YEAR(DATE)) AS 'month_year', count(distinct id_user) AS number
FROM table1
WHERE date between '2020-10-01' and '2020-12-31 23:59:59'
GROUP BY EXTRACT(year_month FROM date)
) sq
GROUP BY 1
Ok guys thanks for your help. The problem was that on the subquery I was pulling the info by month and not by day. So I should pull the info by day there and group by month in the outer query. This finally worked:
SELECT sq.day_month, AVG(number)
FROM (SELECT date(date) AS day_month,
count(distinct id_user) AS number
FROM table_1
WHERE date >= '2020-10-01' AND
date < '2021-01-01'
GROUP BY 1
) sq
GROUP BY EXTRACT(year_month FROM day_month)
Do not use single quotes for column aliases!
SELECT sq.month_year, AVG(number)
FROM (SELECT CONCAT(MONTHNAME(date), '-', YEAR(DATE)) AS month_year,
count(distinct id_user) AS number
FROM table1
WHERE date >= '2020-10-01' AND
date < '2021-01-01'
GROUP BY month_year
) sq
GROUP BY 1;
Note the fixes to the query:
The GROUP BY uses the same columns as the SELECT. Your query should return an error (although it works in older versions of MySQL).
The date comparisons have been simplified.
No single quotes on column aliases.
Note that the outer query is not needed. I assume it is there just to illustrate the issue you are having.
Basically I have a table like this:
Table Time:
ID.......Date
1......08/26/2016
1......08/26/2016
2......05/29/2016
3......06/22/2016
4......08/26/2015
5......05/23/2015
5......05/23/2015
6......08/26/2014
7......04/26/2014
8......08/26/2013
9......03/26/2013
The query should return like this
Year........CountNum
2016........4
2015........3
To find out which year does its value tend to increase in. I notice that I want to display the years that have more values (number of row in this case) than the previous year.
What I've done so far
SELECT Year, count(*) as CountNum
FROM Time
GROUP BY Year
ORDER BY CountNum DESC;
I don't know how to get the year from date format. I tried year(Date) function, but I got Null data.
Please help!
It should works fine.
select year(date), count(*) as countNum
from time
group by year(date)
order by countNum
Join the grouped data to itself with 1 year offset:
select
a.*
from
(
select year(`Date`) as _year, count(*) as _n
from time group by 1
) a
left join
(
select year(`Date`) as _year, count(*) as _n
from time group by 1
) b
on a._year = b._year-1
where a._n > b._n
order by 1
Im currently trying to run a SQL query to export data between a certain date, but it runs the query fine, just not the date selection and i can't figure out what's wrong.
SELECT
title AS Order_No,
FROM_UNIXTIME(entry_date, '%d-%m-%Y') AS Date,
status AS Status,
field_id_59 AS Transaction_ID,
field_id_32 AS Customer_Name,
field_id_26 AS Sub_Total,
field_id_28 AS VAT,
field_id_31 AS Discount,
field_id_27 AS Shipping_Cost,
(field_id_26+field_id_28+field_id_27-field_id_31) AS Total
FROM
exp_channel_data AS d NATURAL JOIN
exp_channel_titles AS t
WHERE
t.channel_id = 5 AND FROM_UNIXTIME(entry_date, '%d-%m-%Y') BETWEEN '01-05-2012' AND '31-05-2012' AND status = 'Shipped'
ORDER BY
entry_date DESC
As explained in the manual, date literals should be in YYYY-MM-DD format. Also, bearing in mind the point made by #ypercube in his answer, you want:
WHERE t.channel_id = 5
AND entry_date >= UNIX_TIMESTAMP('2012-05-01')
AND entry_date < UNIX_TIMESTAMP('2012-06-01')
AND status = 'Shipped'
Besides the date format there is another issue. To effectively use any index on entry_date, you should not apply functions to that column when you use it conditions in WHERE, GROUP BY or HAVING clauses (you can use the formatting in SELECT list, if you need a different than the default format to be shown). An effective way to write that part of the query would be:
( entry_date >= '2012-05-01'
AND entry_date < '2012-06-01'
)
It works with DATE, DATETIME and TIMESTAMP columns.
Consider the following table which has the fields - id (int) and date_created (datetime):
id date_created
1 2010-02-25 12:25:32
2 2010-02-26 13:40:37
3 2010-03-01 12:02:22
4 2010-03-01 12:10:23
5 2010-03-02 10:10:09
6 2010-03-03 12:45:03
I want to know the busiest/most popular hour of the day for this set of data. In this example, the result I'm looking for would be 12.
Ideas?
To get just the most popular hour, use this query
select date_format( date_created, '%H' ) as `hour`
from [Table]
group by date_format( date_created, '%H' )
order by count(*) desc
limit 1;
If you want to look at all the data, go with this one
select count(*) as num_records
, date_created
, date_format( date_created, '%H' ) as `hour`
from [Table]
group by `hour`
order by num_records desc;
If you want something a little more flexible, perhaps to the half hour, or quarter hour, you can do the following:
SELECT floor(time_to_sec(date_created)/3600),count(*) AS period
FROM table GROUP BY period ORDER BY c DESC
If you want the most popular 2 hour interval, use 7200. The most popular 15 minute interval, use 900. You just need to remember you are dealing with seconds (3600 seconds in an hour).
Use the hour() function to extract the hour, then do the usual aggregation:
SELECT count(hour(date_created)) AS c, hour(date_created) AS h FROM table GROUP BY h ORDER BY c DESC;
I like both Simon and Peter's answers, but I can't select both as accepted. I combined the 2 to make a cleaner query that only returned the popular hour (I don't need the counts).
SELECT hour(date_created) AS h
FROM my_table
GROUP BY h
ORDER BY count(*) DESC
LIMIT 1
You could try this:
SELECT
DATE_FORMAT(date,'%H') as hours,
count(*) as count
FROM
myTable
GROUP BY
hours
ORDER BY
count DESC