I have a PnL table with 3 columns. date, region, product.
I'm trying to group all PnL rows by region and product. One way that i've tried is to sum by region and product as following
select PnL : sum(PnL) by region, product from table where date within (d1;d2)
The issue I have is unexpected results. For a given date range (d1;d2) I'm getting the results I'm expecting. However for date range (d1;d2+1) I'm getting 0 everywhere.
I checked the data availability on the d2+1 and data is already available on that day.
Please note that the server is stateless and it is not possible to use intermediate results in variables.
What is the best way to achieve a grouping sum in KDB?
What I am trying to achieve is to get a count of people employed in a particular period.
I have 3 variables:
Employee ID (integer)
Hire date (date)
Termination date (date or null)
Example
the formula I am looking for is something like
if termination_date is null
then
count employee_ID in
dates between Hire_date and max of either hire_date or termination_date
else
count employee ID in
dates between hire_date and termination_date
This aims to show the dynamic of staff level over the time.
I am new to Tableau, not sure how to even start with it. Any suggestions welcome.
This problem will be simpler if you reshape your data to have the following three columns
Employee ID
Date
Action. (where action takes on the values of ‘Hire’ or ‘Terminate’).
Each data row represents one change in status for an employees. If an employee had a termination date, they will have two records in this new format, otherwise just one record showing the hiring date.
You can reshape your data by hand, or leave the original and use Tableau Prep or the Tableau data source page to reshape using a self Union and a few simple calculated fields.
Define a calculated field called Staffing_Change as
if Action=‘Hire’ then 1 else -1 end
Now you can plot the change in staff level over time by putting exact date on columns and sum(Staffing_Change) on Rows. You can use a quick Table calc, Running Sum, to see the net staffing level. For line mark types, I’d use a step style by pressing on the path button on the Marks card. Otherwise, the chart can give the impression of fractional number of employees.
The dashboard in the linked workbook shows a table with sales split by year on the top. Below, there's a table with the rolling average of the last 4 weeks, including the current. It's set to show NULL if there are not enough data points. I'd like for it to compute the first January 2018 value based on the current week and 3 full weeks from the end of 2017. Carrying that concept forward, all NULLs from 2018 onward will be eliminated. The NULLs for the first 5 weeks of 2017 will be the only NULL values. The average should always be computed on a full 4 weeks (28 days) even when week 53 doesn't contain 7 days.
How can I write a calculation to achieve what's described above?
I've tried putting the WINDOW_AVG function inside a LOD, but that's not allowed. Furthermore, I've also tried using FIXED and even FIXED inside WINDOW_AVG.
Here's one of my attempts:
{FIXED [Week_int]:
WINDOW_AVG(SUM([Sales]), -4, 0)
}
It returns this error: "Error: Level of detail expressions cannot contain table calculations or the ATTR function"
Here's the data structure. It includes one value of Sales per day.
Basically I created a dummy data in Excel by creating dates (from 1-1-2017 to 2-2-2021) and filling some random values (unif dist *5000) against these.
I added Week[date] to columns and year[date] to rows as in your screenshot. I added sum(value) on the text marks card.
Thereafter, I added table calculation --> Moving average --> edited it for previous 4 values , next 0 values, (check current value if you want to include current record), then check Null if there are not enough values. (your requirement). --> click compute using -Specific Dimensions change the order of fields below - drag Year above than week (table across then down will also create the same view)
You should be able to get a view as desired.
Regarding your query on number of days in the week, Tableau caters it automatically if you have chosen it datepart.
Edit I verified this in Excel, the method is correctly working.
See, the average of first 28 values in Excel
and the view built in tableau:
Here's the corrected dashboard hosted on Tableau Public.
I'm trying to find a way to create a table like the one above, but instead of having columns of months I would like to have columns of MTD, QTD, YTD for all selected measure values. I created calculated fields on the [Date] field but when I try to use that it still splits the data in to separate columns of months and quarters... I'm using two data sources and they are linked on the [Date] field. If I try to put two of my calculated fields in the columns bar it just combines them like 'MTD/YTD'. How can I get them to display as separate columns?
I know this is strange because there will be overlapping data (everything in the MTD will also be in the QTD and the YTD).
I found a way to do this. I created a calculated field on the date field and assigned 'MTD' to all records from the last month. Then I assigned 'QTD' to all records from the start of the quarter to the day before the start date of the 'MTD' records. Then I assigned 'YTD' to all records from the start of the year to the day before the start of the 'QTD' records. (this way there are no overlapping records).
After that I just did a quick table calc to make each of them a 'running total' table (across).
I created parameters for the dates so the can easily be updated.
If I have a report that tracks data for several accounts for each month with rows labeled:
UNITS,
REVENUE,
AVG REV/UNIT
How would I create a query that will filter the report to just show accounts where the UNITS row has increase/decreased 25% and the AVG REV/UNIT has increased/decreased 10%, from the previous month to the current month.
An example would be for the month of June I have the numbers....
JUN
UNITS 3,271
Revenue $3,598.10
Avg R/U $1.08
So when I run the report at the end of July I only want accounts that have a 25% difference in UNITS and/or a 10% difference in AVG REV/UNIT to show on a report.
qryPharmacy
SELECT PHAR_REPORT.*, (IIf(u1 Is Null,0,u1)+IIf(u2 Is Null,0,u2)+IIf(u3 Is Null,0,u3)+IIf(u4 Is Null,0,u4)+IIf(u5 Is Null,0,u5)+IIf(u6 Is Null,0,u6)+IIf(u7 Is Null,0,u7)+IIf(u8 Is Null,0,u8)+IIf(u9 Is Null,0,u9)+IIf(u10 Is Null,0,u10)+IIf(u11 Is Null,0,u11)+IIf(u12 Is Null,0,u12)) AS USUM, (IIf(r1 Is Null,0,r1)+IIf(r2 Is Null,0,r2)+IIf(r3 Is Null,0,r3)+IIf(r4 Is Null,0,r4)+IIf(r5 Is Null,0,r5)+IIf(r6 Is Null,0,r6)+IIf(r7 Is Null,0,r7)+IIf(r8 Is Null,0,r8)+IIf(r9 Is Null,0,r9)+IIf(r10 Is Null,0,r10)+IIf(r11 Is Null,0,r11)+IIf(r12 Is Null,0,r12)) AS RSUM, RMonth.*, PG2.*, PG.pGroup
FROM PHAR_REPORT, RMonth, PG2, PG
WHERE (((PHAR_REPORT.PR) Like ([PCODE] & '*')) And ((PG.pID)=PG2.PID))
ORDER BY PG2.pID, PHAR_REPORT.PR;
You should do it with more than one query. In the first query, select the data for the first month. On a second, to the desired month to compare. Create a third query that links the two first (be care about the correct relationship). Do the grouping/calculations in these queries.
In the 3rd query, create two fields that calculates increasing/decreasing for units and rev/unit. Now, you can add a criterium on each parameter field in the query columns.
The chalenge here is to be sure about hou would you work with the primary keys on months. Eg: if a A row in the first query isn't in the second (for not having an event on second month, for example), it will not be showed. In this case, the solution would be to create the queryes linking a table or query wich has the entyre set of registers, forcing it to show all the desired records despite they have or not occurrences.