I'm trying to write a SQL Query in MS Access to count the number of times each ID appears in a data set. The data set is formatted as follows:
ID Time
1 12345
1 12346
1 12350
2 99999
2 99999
If the Time for one ID is within 3 seconds of another Time for that same ID, I only want it to be counted once. So the results should look like this:
ID Count
1 2
2 1
The time column is not formatted as a datetime, so I can't use the datediff function. Any help would be appreciated.
This:
SELECT ID, COUNT(newtime)
FROM (SELECT DISTINCT ID, Time\3 AS newtime FROM times)
GROUP BY ID
groups the Time field values in triples using the integer division for Time\3 in Access.
The comment provided by #Andy G worked for my purposes:
"You first need a function to round up (or down) to the nearest multiple of 3. See here (allenbrowne) for example."
I rounded the time values to the nearest multiple of 3, and counted based on that criteria.
Related
I would like to run the below query that looks like this for week 1:
Select week(datetime), count(customer_call) from table where week(datetime) = 1 and week(orderdatetime) < 7
... but for weeks 2, 3, 4, 5 and 6 all in one query and with the 'week(orderdatetime)' to still be for the 6 weeks following the week(datetime) value.
This means that for 'week(datetime) = 2', 'week(orderdatetime)' would be between 2 and 7 and so on.
'datetime' is a datetime field denoting registration.
'customer_call' is a datetime field denoting when they called.
'orderdatetime' is a datetime field denoting when they ordered.
Thanks!
I think you want group by:
Select week(datetime), count(customer_call)
from table
where week(datetime) = 1 and week(orderdatetime) < 7
group by week(datetime);
I would also point out that week doesn't take the year into account, so you might want to include that in the group by or in a where filter.
EDIT:
If you want 6 weeks of cumulative counts, then use:
Select week(datetime), count(customer_call),
sum(count(customer_call)) over (order by week(datetime)
rows between 5 preceding and current row) as running_sum_6
from table
group by week(datetime);
Note: If you want to filter this to particular weeks, then make this a subquery and filter in the outer query.
I have table which updates on weekly basis, I need to check count variation check between one week and previous week values. I just did below....
Select
case when F.wk_end_d=max(F.wk_end_d) over (partition by F.wk_end_d)then F.the_count end as count
from
(
select wk_end_d, count(*) as the_count
from table A
where wk_end_d between date_sub('2019-03-02',7) and '2019-03-02'
group by wk_end_d
) F
which give me value like below
100
200
but I need get value like 100 200 on 2 different columns as I need build some other calculations on top of it.
I'm trying to write a SQL query that will query my table, then in the result set for one of the columns return a different, incrementing value, but for duplicates it would have the same value. I'm having trouble finding the right words to explain it but an example should clear it up. Here's an example table:
Date ActionTaken UserID
2017-12-5 Update 1
2017-12-6 Add 1
2017-12-6 Delete 1
2017-12-7 Update 1
2017-12-8 Update 1
2017-12-8 Delete 1
And when I do my query, I'd like the result to be something like:
Date ActionTaken UserID
Day 1 Update 1
Day 2 Add 1
Day 2 Delete 1
Day 3 Update 1
Day 4 Update 1
Day 4 Delete 1
ActionTaken and UserID data are irrelevant, I'd just like to be able to group by values in the Date Column, then assign them a new value with an incrementing number, grouping rows with the same Date value to have the same number.
I think you want dense_rank():
select dense_rank() over (order by date) as seqnum,
. . .
from t;
This returns a number. You can, at your leisure, add date before the number.
It is a mystery to me with this text book example. We have simply:
Transaction_ID (primary key), Client_ID, Transaction_Amount, Month
1 1 500 1
2 1 1000 1
3 1 10 2
4 2 11 2
5 3 300 2
6 3 10 2
... ... ... ...
I want to calculate in SQL the mean(Transaction_Amount), std(Transaction_Amount) and the some percentile(Transaction amount) grouped by Client_ID. But is seems, even given that percentile is a very similar calculation than the standard deviation, SQL cannot do it with a simple statement as:
SELECT
mean(Transaction_Amount),
std(Transaction_Amount),
percentile(Transaction_Amount)
FROM
myTable
GROUP BY
Client_ID, Month
Or can it?
It gets worse becuase I also need to Group By Month in addition to Client_ID.
Thanks a lot!
Sven
I'm sure Oracle can do the calculations you want. I just don't know what they are. You specify that you want something grouped by ClientId. Yet, your sample query has two keys in the GROUP BY.
Some functions that you want to look at are:
AVG()
STDDEV()
PERCENT_RANK()
Without sample data and desired results (or a very clear explanation of what you are trying to calculate), I can't put together a query.
The title is a bit confusing but I'll explain my problem here:
So i have a database table with millions of lines of spending data broken up into different time fields (period1 - period14). Now what i need to do is write a query that will return the records where the spending in one period is equal to the spending in a different period within the same record. So basically that means if i have a reecord where the spending in period1 is $100 and then the spending in period5 is also $100, it will add that record to a new table. I tried something like the code below but since I'm very new to access it is rather complex/inefficient and also doesn't do what i need it to.
INSERT INTO Contracts
SELECT *
FROM SPENDDETAIL
WHERE (SPENDDETAIL.Period1 = SPENDDETAIL.Period2 OR SPENDDETAIL.Period3 [...] OR SPENDDETAIL.Period14)
AND (SPENDDETAIL.Period1 <> 0 OR SPENDDETAIL.Period2 <> 0 [...] OR SPENDDETAIL.Period14 <> 0);
Any help much appreciated, thanks!
Oh also i know this code snippet would only return the records where the period1 spend equals the spend from any of the other periods it was just a beginning attempt at making the query do what i need it to.
Something along these lines might get you started:
SELECT Id, Value, COUNT(*) FROM
(SELECT Id AS Id, 1 AS Period, Period1 AS Value FROM SPENDDETAIL
UNION ALL
SELECT Id AS Id, 2 AS Period, Period2 AS Value FROM SPENDDETAIL
UNION ALL
SELECT Id AS Id 3 AS Period, Period3 AS Value FROM SPENDDETAIL
etc...) x
GROUP BY Id, Value
HAVING COUNT(*) > 1
Where Id is some unique identifier for each row of the data (assuming there is such a thing).
This will give you a list of Ids and matching values.