I think what I am trying to do is probably super simple. My use of SQL is just different until now.
I have a list of accounts that are opened all time. I would like to count how many accounts are opened by week. Monday-Sunday. Since the start of tracking.
Account | Signup Date
---------------------
1 | 1/1/17
2 | 1/6/17
3 | 1/10/17
4 | 1/13/17
5 | 2/4/17
6 | 2/5/17
7 | 3/15/17
So ideally if every week of the year starting 1/1/17 is numbered 1-53 I would love to be able to get 1 count of how many accounts signed up each week.
If that possible I would love any help.
the mysql function week(date) will help you. Or the SQLServer DATEPART( wk, date)
SELECT week(Signup Date,3) as 'Week',
count(Account) as 'Accounts Created'
FROM table
GROUP BY week(Signup Date,3)
Shoud give you the desired result
Related
I don't think I properly titled this, but in essence I'm wanting to be able to count distinct users but have those previous distinct users be considered as time goes on. As an example, say we have a dataset of user purchases over time:
Date | User
-----------------
2/3/22 | A
2/4/22 | B
2/22/22 | C
3/2/22 | A
3/4/22 | D
3/15/22 | A
4/30/22 | B
Generally, if I were to count distincts grouped by months as would be normal we would get:
Date | Count
-----------------
2/1/22 | 3
3/1/22 | 2
4/1/22 | 1
But what I'm really wanting to see would be how the total number of distinct users increases over the time period.
Date | Count
-----------------
2/1/22 | 3
3/1/22 | 4
4/1/22 | 4
As such it would be 3 distinct users for the first month. Then 4 for the second month considering the total number of distinct users grew by one with the addition of "D" while "A" isn't counted because it was already recognized as a distinct user in the previous month. The third month would then still be 4 because no new distinct user performed an action that month.
Any help would be greatly appreciated (even if it is just a better title so that it reaches more people more appropriately haha)
here's a solution based on running sum in Postgres that should translate well to Vertica.
select date_trunc('month', "Date") as "Date"
,sum(count(case rn when 1 then 1 end)) over (order by date_trunc('month', "Date")) as "Count"
from (
select "Date"
,"User"
,row_number() over(partition by "User" order by "Date") as rn
from t
) t
group by date_trunc('month', "Date")
order by "Date"
Date
Count
2022-02-01 00:00:00
3
2022-03-01 00:00:00
4
2022-04-01 00:00:00
4
Fiddle
How can I get all IDs that have more than 10 entries on one day?
Here is the sample data:
ID | Time
__________________________
4 | 2019-02-14 17:22:43
__________________________
2 | 2019-04-27 07:51:09
__________________________
83 | 2018-01-07 08:38:37
__________________________
I am having a hard time using count and going through and finding all of the ones on the same day. The Hour:Min:Sec is what is causing problems for me.
For MySql it would be:
select distinct id from tablename
group by id, date(time)
having count(*) > 10
The date() function rejects the time part of the column, so the grouping is done only by the date part.
For SqlServer you would use:
convert(date, time)
I am currently trying to accomplish the following:
get the Last Weekstamp for the last 6 Months, the following ilustrates how the end result might look like:
Month | Weekstamp |
2013-12| 2013-52 |
2014-01| 2014-05 |
.... and so on
I have a auxiliary Table, which has all Weeks in it and allows me to connect to a Calender Table, which in turn has all months, meaning i am able to get all weekstamps per Month,
but how do i get all of the Last Week Numbers for the Last 6 Months ?
my idea was a Temporary table of some sor (never used one, am a beginner when it Comes to SQL)
which calculates all of the Weekstamps needing to be filtered out per month, and than gives out only values which i could than use to filter a query which contains all the data i Need.
Anybody have a better idea?
As i said I am just a beginner so i can't really say what the best way would be
Thanks a lot in Advance!
My guess is that your challenge is determining what the last six months are. To do this you can use a tally table (spt_values) and DateDiff to determine when the last six months are.
You can also depending on which DB and version easily do this without a calander or weeks table.
This
WITH rnge
AS (SELECT number
FROM master..spt_values
WHERE type = 'P'
AND number > 0
AND number < 7),
dates
AS (SELECT EOMONTH(Dateadd(m, number * -1, Getdate())) dt
FROM rnge)
SELECT Year(dt) year,
Month(dt) month,
Datepart(wk, dt) week
FROM dates
Produces this output
| YEAR | MONTH | WEEK |
|------|-------|------|
| 2014 | 1 | 5 |
| 2013 | 12 | 53 |
| 2013 | 11 | 48 |
| 2013 | 10 | 44 |
| 2013 | 9 | 40 |
| 2013 | 8 | 35 |
Demo
I'll leave it to you to format the values
This assumes SQL Server 2012 since it uses EOMONTH see Get the last day of the month in SQL for previous versions of SQL Server
I have a table:
ID | Name | TDate
1 | John | 1 May 2013, 8:67AM
2 | Jack | 2 May 2013, 6:43AM
3 | Adam | 3 May 2013, 9:53AM
4 | Max | 4 May 2013, 2:13AM
5 | Leny | 5 May 2013, 5:33AM
I need a query that will return all the items where TDate is a weekend. How would I write such a
query?
WHAT I HAVE SO FAR
select
table.*,
EXTRACT (DAY FROM table.tdate )
from table
I did a select using EXTRACT to just see if I can get the right values. However, EXTRACT with the parameter DAY returns the day of the month. If I instead use WEEKDAY, as per the documentation here, then I get error:
ERROR: timestamp units "weekday" not recognized
SQL state: 22023
limit 1250
EDIT
TDate has a data type of datetime (timestamp). I just wrote it like that for easy reading. But regardless of the type, I could easily cast between types if need be.
I know dates 4May and 5May are weekends (as they fall on a Saturday and a Sunday). Does firebird allow for a way to write a query that will return dates if they fall on weekends.
try this:
SELECT ID, Name, TDate
FROM your_table
WHERE EXTRACT(WEEKDAY FROM TDate) IN (6,0)
UPDATE
condition must be (0,6) not (0,1).
I have a table that reflects a monthly census of a certain population. Each month on an unpredictable day early in that month, the population is polled. Any member who existed at that point is included in that month's poll, any member who didn't is not.
My task is to look through an arbitrary date range and determine which members were added or lost during that time period. Consider the sample table:
ID | Date
2 | 1/3/2010
3 | 1/3/2010
1 | 2/5/2010
2 | 2/5/2010
3 | 2/5/2010
1 | 3/3/2010
3 | 3/3/2010
In this case, member with ID "1" was added between Jan and Feb, and member with ID 2 was lost between Feb and Mar.
The problem I am having is that if I just poll to try and find the most recent entry, I will capture all the members that were dropped, but also all the members that exist on the last date. For example, I could run this query:
SELECT
ID,
Max(Date)
FROM
tableName
WHERE
Date BETWEEN '1/1/2010' AND '3/27/2010'
GROUP BY
ID
This would return:
ID | Date
1 | 3/3/2010
2 | 2/5/2010
3 | 3/3/2010
What I actually want, however, is just:
ID | Date
2 | 2/5/2010
Of course I can manually filter out the last date, but since the start and end date are parameters I want to generalize that. One way would be to run sequential queries. In the first query I'd find the last date, and then use that to filter in the second query. It would really help, however, if I could wrap this logic into a single query.
I'm also having a related problem when I try to find when a member was first added to the population. In that case I'm using a different type of query:
SELECT
ID,
Date
FROM
tableName i
WHERE
Date BETWEEN '1/1/2010' AND '3/27/2010'
AND
NOT EXISTS(
SELECT
ID,
Date
FROM
tableName ii
WHERE
ii.ID=i.ID
AND
ii.Date < i.Date
AND
Date BETWEEN '1/1/2010' AND '3/27/2010'
)
This returns:
ID | Date
1 | 2/5/2010
2 | 1/1/2010
3 | 1/1/2010
But what I want is:
ID | Date
1 | 2/5/2010
I would like to know:
1. Which approach (the MAX() or the subquery with NOT EXISTS) is more efficient and
2. How to fix the queries so that they only return the rows I want, excluding the first (last) date.
Thanks!
You could do something like this:
SELECT
ID,
Max(Date)
FROM
tableName
WHERE
Date BETWEEN '1/1/2010' AND '3/27/2010'
GROUP BY
ID
having max(date) < '3/1/2010'
This filters out anyone polled in March.