I am new to sql and this is my first ever question. I am working with a sample database that I want to extract specific information from to display as a dashboard. The issue is that I can do this partially but I cannot seem to figure it out properly.
``SELECT
S_date as date,
p_time as time,
process_id as process,
sc_gun as scannumb,
sum(line_qty) as linetotal,
sum(area_qty) as areatotal
FROM dbfile6
WHERE
process_id in('0010','0020','0030')
and sc_gun in = ('10','20','30','40','50')
and s_date = curdate() - 1 and p_time between '22:00:00' and '23:59:59'
or s_date = curdate() and p_time between '00:00:00' and '06:00:00'
GROUP BY p_time, s_date, process_id, sc_gun
ORDER BY s_date, process_id
What do I want to display?
I can do partially where I want it to work to yesterdays date (s_date) recurring but I want this to only happen Monday to Friday, skipping the weekend so when we are on Monday, it looks at Fridays data from the database.
I want to show the time as a range, a night range. The range is 20:00:00 - 06:00:00. The range is tricky as it crosses over to the next day, this could work for Monday to Thursday but not Friday as there is no working weekend so what would I do here? In addition to this, I can sum up the values successfully and display it as averages for each process but then once I add the time in, it displays each result individually.
The table below is what it looks like in the database, however as mentioned earlier, the desired result is for each process to have the line_qty and area_qty summed up by time range and a day and night cycle.
s_date
p_time
process_id
sc_gun
line_qty
area_qty
04/05/2022
04:49:52
0010
10
2
12
03/05/2022
11:50:00
0010
10
5
14
03/05/2022
19:50:00
0010
10
7
16
03/05/2022
13:50:00
0020
20
4
6
03/05/2022
19:50:00
0010
10
7
16
Related
I"m dealing with a dataset with 4 week sales data (data will be refreshed every hour) and need to observer for abnormality
I think I'll go with a basic approach, to compare with average numbers and I'm trying to figure out how to best break this down so I can answer some questions below
On average, how many orders received at 9:00 , 15:00 or 16:00 past 30 days
On average, how many orders received at 9:00 every Wednesday (past 4 Wednesdays), at 15:00 every Thursday (past 4 Thursdays),
Not sure how do we go about this (after breaking date/time down to Hour and Weekday columns)
date
order ID
order hour
order weekday
10/07/2022 10:26:12 PM
1111
22
6
10/07/2022 10:27:12 PM
2222
22
6
....
....
....
....
19/07/2022 11:34:19 AM
9998
11
1
19/07/2022 11:34:35 AM
9999
11
1
I would love to get your advice please
Thanks
I've ended up going with a tedious approach.
#get current hour & weekday
now=datetime.datetime.now()
today=datetime.date.today()
current_hour=now.hour
current_weekday=today.weekday()
#create a DF with orders from the same hour & weekday window
same_hour_weekday_df=order_df[(order_df.order_hour==current_hour ) & (order_df.order_weekday==current_weekday) ]
#calculate avg orders generated from the past weeks within the same hour and weekyday timeframe
orders_same_hour_weekday=same_hour_weekday_df['order_created_at'].count()
same_hour_weekday_periods=same_hour_weekday_df['order_week'].nunique()
avg_orders_same_hour_weekday=orders_same_hour_weekday/same_hour_weekday_periods
I have date field and from that date field i am trying to extract only weekends i.e. in my case Saturday and Sunday is weekend.
So how can i extract weekends from date?
If below dates are in weekend then should be like this:
Date day working hours
01/01/2019
02/01/2019
03/01/2019
04/01/2019
05/01/2019 weekend 24
06/01/2019 weekend 87
07/01/2019
08/01/2019
09/01/2019
10/01/2019
Data link: https://www.dropbox.com/s/xaps82qyyo6i0fa/ar.xlsx?dl=0
You can use WeekDay functon. This function accepts date value/field and return the day of the week. The returned value is in dual format - day name and day number.
So you can create additional field that checks if the day number is >= 5 (day numbers are starting from 0 so Saturday = 5 and Sunday = 6)
RawData:
LOAD
AttendanceDay,
if(WeekDay(AttendanceDay) >= 5, 1, 0) as isWeekend,
Employee_ID,
WorkingHours
FROM
[..\Downloads\ar.xlsx]
(ooxml, embedded labels, table is Attendances_20191119_0838)
;
Resulted table after the reload:
I have the below set of data which represents employee sick/absence days over a period (12 months) of time, in a table named Absence:
Day Date DaysSick OccasionsSick Notes
Tuesday 2016-09-27 1 Lisa A working today
Thursday 2016-09-29 1 Lisa sick today Celeste
Thursday 2017-01-05 1 Lisa sick today
I would like to update the OccasionsSick column based upon the instances of being sick. So i would have the following:
Day Date DaysSick OccasionsSick Notes
Tuesday 2016-09-27 1 1 Lisa A working today
Thursday 2016-09-29 1 Lisa sick today Celeste
Thursday 2017-01-05 1 1 Lisa sick today
So, the first two entries are the same period of sick leave, so i need a 1 in the first row, and the last entry is a separate sick period, so a 1 again.
Now, in order to establish a sick period there would be a reference to a roster table containing the below:
Date RosterType
2016-09-27 Sick
2016-09-28 Day Off
2016-09-29 Sick
2016-09-30 Normal
So the 27th and 29th were sick days, but the 28th was a standard day off, which is a likely occurrence, so using consecutive days is not an option. I need to be able to look for sick days until a "normal" RosterType is found, this then breaks the sick period. This 1 then needs to be assigned as per the desired result set.
What is the best way of updating the data here? I have come up with a big blank on this, apart from the logic of determining a sick period.
I am presenting this data in Excel with VBA, so it could also be easier to assign the sick periods in VBA, as opposed to SQL for the raw data
Please check this out.
This assumes that there is an entry in the roster for each day.
Basically I'm just building a period and counting the days in the roster.
If there are normal days in between it counts as a new period.
WITH CTE AS (
SELECT
[day]
,[date]
,LAG(date, 1) over (order by date) datebefore
,[dayssick]
FROM [dbo].[absence]
)
SELECT
*
,CASE WHEN ((SELECT COUNT(1) FROM [dbo].[rostertype] WHERE date < c.date AND date > c.datebefore AND rostertype = 'Normal') > 0
OR c.datebefore IS NULL) THEN 1 ELSE 0 END OccasionsSick
FROM CTE c
I have a table where our product records its activity log. The product starts working at 23:00 every day and usually works one or two hours. This means that once a batch started at 23:00, it finishes about 1:00am next day.
Now, I need to take statistics on how many posts are registered per batch but cannot figure out a script that would allow me achiving this. So far I have following SQL code:
SELECT COUNT(*), DATEPART(DAY,registrationtime),DATEPART(HOUR,registrationtime)
FROM RegistrationMessageLogEntry
WHERE registrationtime > '2014-09-01 20:00'
GROUP BY DATEPART(DAY, registrationtime), DATEPART(HOUR,registrationtime)
ORDER BY DATEPART(DAY, registrationtime), DATEPART(HOUR,registrationtime)
which results in following
count day hour
....
1189 9 23
8611 10 0
2754 10 23
6462 11 0
1885 11 23
I.e. I want the number for 9th 23:00 grouped with the number for 10th 00:00, 10th 23:00 with 11th 00:00 and so on. How could I do it?
You can do it very easily. Use DATEADD to add an hour to the original registrationtime. If you do so, all the registrationtimes will be moved to the same day, and you can simply group by the day part.
You could also do it in a more complicated way using CASE WHEN, but it's overkill on the view of this easy solution.
I had to do something similar a few days ago. I had fixed timespans for work shifts to group by where one of them could start on one day at 10pm and end the next morning at 6am.
What I did was:
Define a "shift date", which was simply the day with zero timestamp when the shift started for every entry in the table. I was able to do so by checking whether the timestamp of the entry was between 0am and 6am. In that case I took only the date of this DATEADD(dd, -1, entryDate), which returned the previous day for all entries between 0am and 6am.
I also added an ID for the shift. 0 for the first one (6am to 2pm), 1 for the second one (2pm to 10pm) and 3 for the last one (10pm to 6am).
I was then able to group over the shift date and shift IDs.
Example:
Consider the following source entries:
Timestamp SomeData
=============================
2014-09-01 06:01:00 5
2014-09-01 14:01:00 6
2014-09-02 02:00:00 7
Step one extended the table as follows:
Timestamp SomeData ShiftDay
====================================================
2014-09-01 06:01:00 5 2014-09-01 00:00:00
2014-09-01 14:01:00 6 2014-09-01 00:00:00
2014-09-02 02:00:00 7 2014-09-01 00:00:00
Step two extended the table as follows:
Timestamp SomeData ShiftDay ShiftID
==============================================================
2014-09-01 06:01:00 5 2014-09-01 00:00:00 0
2014-09-01 14:01:00 6 2014-09-01 00:00:00 1
2014-09-02 02:00:00 7 2014-09-01 00:00:00 2
If you add one hour to registrationtime, you will be able to group by the date part:
GROUP BY
CAST(DATEADD(HOUR, 1, registrationtime) AS date)
If the starting hour must be reflected accurately in the output (as 9, 23, 10, 23 rather than as 10, 0, 11, 0), you could obtain it as MIN(registrationtime) in the SELECT clause:
SELECT
count = COUNT(*),
day = DATEPART(DAY, MIN(registrationtime)),
hour = DATEPART(HOUR, MIN(registrationtime))
Finally, in case you are not aware, you can reference columns by their aliases in ORDER BY:
ORDER BY
day,
hour
just so that you do not have to repeat the expressions.
The below query will give you what you are expecting..
;WITH CTE AS
(
SELECT COUNT(*) Count, DATEPART(DAY,registrationtime) Day,DATEPART(HOUR,registrationtime) Hour,
RANK() over (partition by DATEPART(HOUR,registrationtime) order by DATEPART(DAY,registrationtime),DATEPART(HOUR,registrationtime)) Batch_ID
FROM RegistrationMessageLogEntry
WHERE registrationtime > '2014-09-01 20:00'
GROUP BY DATEPART(DAY, registrationtime), DATEPART(HOUR,registrationtime)
)
SELECT SUM(COUNT) Count,Batch_ID
FROM CTE
GROUP BY Batch_ID
ORDER BY Batch_ID
You can write a CASE statement as below
CASE WHEN DATEPART(HOUR,registrationtime) = 23
THEN DATEPART(DAY,registrationtime)+1
END,
CASE WHEN DATEPART(HOUR,registrationtime) = 23
THEN 0
END
My initial answer to this problem has been to script it. Instead of using SQL, I've dipped into Python and normalised them. I am curious whether anyone can come up with a solution using SQL though.
If a date occurs outside of business hours, I want to normalise the date to the next working day. I'll keep this really simple and say that business hours is 9am to 6pm Monday to Friday. Anything outside of those hours is outside of business hours.
What should happen the dates is that they are changed so that 2pm on Saturday becomes 9am on Monday morning (the first legitimate time in the business week). 7pm on a Wednesday becomes 9am Thursday morning. etc. etc. Let's ignore holidays.
Sample data:
mysql> select mydate from mytable ORDER by mydate;
+---------------------+
| mydate |
+---------------------+
| 2009-09-13 17:03:09 |
| 2009-09-14 09:45:49 |
| 2009-09-15 09:57:28 |
| 2009-09-16 21:55:01 |
+---------------------+
4 rows in set (0.00 sec)
The first date is a Sunday so it should be normalised to 2009-09-14 09:00:00
The second date is fine, it's at 9am on a Monday.
The third date is fine, it's at 9am on a Tuesday.
The fourth date is at 9pm (outside of our 9am to 6pm business hours) on a Wednesday and should be transformed to 9am Thursday morning.
I think you're better off with your Python solution ... but I like challenges :)
select mydate
, case dayadjust
-- BUG
-- when 0 then mydate
-- BUG
when 0 then case
when hour(mydate)<9
then date_add(from_days(to_days(mydate)),
INTERVAL 9 HOUR)
else mydate
end
-- BUG SQUASHED
else date_add(from_days(to_days(mydate) + dayadjust),
INTERVAL 9 HOUR)
end as mynewdate
from (
select mydate
, case
when addday>=moreday then addday
else moreday
end as dayadjust
from (
select mydate
, weekday(mydate) as w
, hour(mydate) as h
, case weekday(mydate)
when 6 then 1
when 5 then 2
when 4 then
case
when hour(mydate) >= 18 then 3
else 0
end
else 0
end as addday
, case when hour(mydate)>=18 then 1 else 0 end as moreday
from mytable
order by mydate
) alias1
) alias2
Tested on MySQL
$ mysql tmp < phil.sql
mydate mynewdate
2009-09-12 17:03:09 2009-09-14 09:00:00
2009-09-12 21:03:09 2009-09-14 09:00:00
2009-09-13 17:03:09 2009-09-14 09:00:00
2009-09-14 09:45:49 2009-09-14 09:45:49
2009-09-15 09:57:28 2009-09-15 09:57:28
2009-09-16 21:55:01 2009-09-17 09:00:00
2009-09-17 11:03:09 2009-09-17 11:03:09
2009-09-17 22:03:09 2009-09-18 09:00:00
2009-09-18 12:03:09 2009-09-18 12:03:09
2009-09-18 19:03:09 2009-09-21 09:00:00
2009-09-19 06:03:09 2009-09-21 09:00:00
2009-09-19 16:03:09 2009-09-21 09:00:00
2009-09-19 19:03:09 2009-09-21 09:00:00
Not sure why you want to do this, but if it needs to always be true of all data in your database, you need a trigger. I would set up a table to pull from that specifies the business hours and you can use that table to determine the next valid business hour day and time. (I might even consider making a table that tells you exactly what the next business day and hour is for each possibility, it's not like this changes a lot, might have to be updated once a year if you change holidays for the next year or if you change the overall business hours. By precalulating, you can probably save time in processing this.). I would also conmtinue to use your script becasue it's better to fix data before it gets entered, but you need the trigger to ensure that data from any source (and sooner or later there will be changes form sources other than your application) meets the data integrity rules.
I don't think you can do it in one query, but you can try this:
-- Mon-Thu, after 17:00
-- Set date = next day, 9:00
UPDATE
myTable
SET
mydate = DATE_ADD(DATE_ADD(DATE(date), INTERVAL 1 DAY), INTERVAL 9 HOUR)
WHERE
TIME(mydate) >= 17
AND DAYOFWEEK(mydate) IN (1,2,3,4)
-- Mon-Fri, before 9:00
-- Set date = the same day, 9:00
UPDATE
myTable
SET
mydate = DATE_ADD(DATE(date), INTERVAL 9 HOUR)
WHERE
TIME(mydate) < 9
AND DAYOFWEEK(mydate) IN (1,2,3,4,5)
-- Fri, after 17:00, Sat, Sun
-- Set date = monday, 9.00
UPDATE
myTable
SET
mydate = DATE_ADD(DATE_ADD(DATE(date), INTERVAL 3 DAY), INTERVAL 9 HOUR)
WHERE
(TIME(mydate) >= 17
AND DAYOFWEEK(mydate) = 5)
OR DAYOFWEEK(mydate) IN (6,7)