I'm trying to create a query that will show the properties that were sold and were on the market for less than 6 weeks. In the listings table, there is BeginListDate and EndList Date.
So far my WHERE statement looks like
WHERE SaleStatus.Salestatus = 'Sold' AND DATEDIFF(YEAR,BeginListDate, EndListDate) >42
but that query is incorrect. I'm just confused on how to write a where statement where it only considers those that were on the market for less than 6 weeks.
Just to elaborate on #JamieD77's very correct comment...
Your condition:
DATEDIFF(YEAR,BeginListDate, EndListDate) >42
Says "The number of Years between the BeginListDate and the EndListDate is greater than 42". That's a hell of a long list period. You say you are looking for the the list period to be less than 42 days, so #JamieD77's suggestion to:
Datediff(day,BeginListDate, EndListDate) < 42
Is the right way to go. This says "The number of Days between beginlistdate and endlistdate is less than 42."
The difference here is the DatePart as #squillman suggested changing from Year to Day as well as the inequality itself. You wanted Less Than, <.
Hint but depended on how would you preferred in report or project.
this example and if both startdate and endate are in the same calendar week, the return value for week would be 0.
select DATEDIFF(week,getdate(),getdate()+7)
it has been consider week start for sunday based on system.
Related
Let me start by saying that I am somewhat new to SQL/Snowflake and have been putting together queries for roughly 2 months. Some of my query language may not be ideal and I fully understand if there's a better, more efficient way to execute this query. Any and all input is appreciated. Also, this particular query is being developed in Snowflake.
My current query is pulling customer volumes by department and date based on a 45 day window with a 24 day lookback from current date and a 21 day look forward based on scheduled appointments. Each date is grouped based on where it falls within that 45 day window: current week (today through next 7 days), Week 1 (forward-looking days 8-14), and Week 2 (forward-looking days 15-21). I have been working to try and build out a comparison column that, for any date that lands within either the Week 1 or Week 2 group, will pull in prior period volumes from either 14 days prior (Week 1) or 21 days prior (Week 2) but am getting nowhere. Is there a best-practice for this type of column? Generic example of the current output is attached. Please note that the 'Prior Wk' column in the sample output was manually populated in an effort to illustrate the way this column should ideally work.
I have tried several different iterations of count(case...) similar to that listed below; however, the 'Prior Wk' column returns the count of encounters/scheduled encounters for the same day rather than those that occurred 14 or 21 days ago.
Count(Case When datediff(dd,SCHED_DTTM,getdate())
between -21 and -7 then 1 else null end
) as "Prior Wk"
I've tried to use an IFF statement as shown below, but no values return.
(IFF(ENCOUNTER_DATE > dateadd(dd,8,getdate()),
count(case when ENC_STATUS in (“Phone”,”InPerson”) AND
datediff(dd,ENCOUNTER_Date,getdate()) between 7 and 14 then 1
else null end), '0')
) as "Prior Wk"
Also have attempted creating and using a temporary table (example included) but have not managed to successfully pull information from the temp table that didn't completely disrupt my encounter/scheduled counts. Please note for this approach I've only focused on the 14 day group and have not begun to look at the 21 day/Week 2 group. My attempt to use the temp table to resolve the problem centered around the following clause (temp table alias: "Date1"):
CASE when AHS.GL_Number = "DATEVISIT1"."GL_NUMBER" AND
datevisit1.lookback14 = dateadd(dd,14,PE.CONTACT_Date)
then "DATEVISIT1"."ENC_Count"
else null end
as "Prior Wk"*
I am extremely appreciative of any insight on the current best practices around pulling prior period data into a column alongside current period data. Any misuse of terminology on my part is not deliberate.
I'm struggling to understand your requirement but it sounds like you need to use window functions https://docs.snowflake.com/en/sql-reference/functions-analytic.html, in this case likely a SUM window function. The LAG window function, https://docs.snowflake.com/en/sql-reference/functions/lag.html, might also be of some help
I have a simple income and covers served per day report, I need to calculate the variance % difference between this years income and last years income, but excluding any sites that opened this year.
I have the following expression however the results it returns are way out from what I am expecting:
=sum(iif(Fields!New_Site.Value=False And Fields!netSalesLY.Value<>0,CDbl(Fields!netSalesTY.Value/Fields!netSalesLY.Value),CDbl(0)))
New_Site is a Boolean parameter to filter out new/old sites, and both netsalesTY and netsalesLY are integer values.
Any ideas?
Thanks
The first thing I notice is that you're not referencing the New_Site parameter, you're referencing the New_Site field in your formula. If you wanted to reference the New_Site parameter, you would do it as
Parameters!New_Site.value
Not sure which you are really wanting to use.
Also, I may be misunderstanding what number you're trying to calculate, but if I understand you correctly, you're using the wrong formula. You're not using the percent difference formula, which will return the percent of this years sales related to last years sales, not a difference between the two. If what you want to know is the percent difference between the two years, it would be calculated as:
(Fields!netSalesTY.Value - Fields!netSalesLY.Value) / Fields!netSalesLY.Value
So if last year your netSales were $100,000 and this year they are $85,000, your current formula would return 85%, whereas the formula I just mentioned would return -15%, thus showing the decline in sales. So with the formula I gave you, a negative number would represent a decrease from last year to this year and a positive number would represent an increase from last year to this year.
Hope this helps!
I am wondering if it's possible (without actually parsing the given string) to get the actual range (in terms of days, minutes or seconds) that is specified when you have an SQL statement like
[select 'x'
from dual
where date between to_date('20111113152049')
and to_date('20120113152049')]
I am working on a query where I'm given a string in the form of
"between to_date(A) and to_date(B)"
and would like to get that value in days to compare to a policy we let the user set so they don't enter a date range longer than say a week.
Assuming you're looking for a theoretical answer (that is: don't take this into production) this could work:
Prerequistes:
have three tables: days_seq(day_seq), month_seq(mth_seq) and year_seq(yr_seq)
days has the numbers 1...31, month 1..12, years 2011....?
Use te following query (I used access because I don't have proper RDBMS available here, keep in mind that MS-ACCESS/JET is forgiving in the use of the Dateserial function, that is, it doesn't break when you ask the dateserial for february, 30th, 2012)
SELECT Max(DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
, [days_seq]![day_seq]))
-
Min(DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
,[days_seq]![day_seq])) AS days
FROM days_seq, month_seq, year_seq
WHERE DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
,[days_seq]![day_seq])
BETWEEN #2012-02-1# AND #2012-02-28#
The query basically produces a carthesian product of three tables which generates all possible days in months, months in a year for as many years as you have in the years table.
Bonus:
You could off-course generate a permanent Calendar table as X-Zero suggests.
table calendar([date])
INSERT INTO calendar
SELECT DISTINCT DateSerial(
[year_seq]![yr_seq]
,[month_seq]![mth_seq]
, [days_seq]![day_seq]))
FROM days_seq, month_seq, year_seq
You still have to pick your start year and your end year wisely. According to the Maya's an enddate of december 21st, 2012 will do.
Suppose ,I have a table which has all the billing records. Now I want to see the sales trend for a user given time duration group by each 3 days ...what should be the sql query regarding this?
please help,Otherwise I am gone ...
I can only give a vague suggestion as per the question, however you may want to have a derived column with a standardised date (as per MS date format, just a number per day) that you could then use a modulus (3) on so that days are equal per 3 day period. You can then group and aggregate over this column to get the values for a 3 day period. Obviously to display the date nicely you would have to multiply back and convert your column as well.
Again I'm not sure of the specifics, but I think this general idea could be achieved to get a result (may well not be the best way so it would help to add more to the question...)
I have an SQLite database with the following fields for example:
date (yyyymmdd fomrat)
total (0.00 format)
There is typically 2 months of records in the database. Does anyone know a SQL query to find a weekly average?
I could easily just execute:
SELECT COUNT(1) as total_records, SUM(total) as total FROM stats_adsense
Then just divide total by 7 but unless there is exactly x days that are divisible by 7 in the db I don't think it will be very accurate, especially if there is less than 7 days of records.
To get a daily summary it's obviously just total / total_records.
Can anyone help me out with this?
You could try something like this:
SELECT strftime('%W', thedate) theweek, avg(total) theaverage
FROM table GROUP BY strftime('%W', thedate)
I'm not sure how the syntax would work in SQLite, but one way would be to parse out the date parts of each [date] field, and then specifying which WEEK and DAY boundaries in your WHERE clause and then GROUP by the week. This will give you a true average regardless of whether there are rows or not.
Something like this (using T-SQL):
SELECT DATEPART(w, theDate), Avg(theAmount) as Average
FROM Table
GROUP BY DATEPART(w, theDate)
This will return a row for every week. You could filter it in your WHERE clause to restrict it to a given date range.
Hope this helps.
Your weekly average is
daily * 7
Obviously this doesn't take in to account specific weeks, but you can get that by narrowing the result set in a date range.
You'll have to omit those records in the addition which don't belong to a full week. So, prior to summing up, you'll have to find the min and max of the dates, manipulate them such that they form "whole" weeks, and then run your original query with a WHERE that limits the date values according to the new range. Maybe you can even put all this into one query. I'll leave that up to you. ;-)
Those values which are "truncated" are not used then, obviously. If there's not enough values for a week at all, there's no result at all. But there's no solution to that, apparently.