I had the following question which I just can't wrap my head around it to do it in a neat way.
I want to create a line graph with three lines. We call it a budget snake.
Created sales orders (black)
Invoiced orders (green)
Daily targets (red)
This per salesperson. The creation of this graph for the created and invoiced orders is easy as these are all on a daily granularity so creating the line graph is easy.
I just struggle how to create/generate such a line for the targets.
In this case, I manually created a table with date - salesperson - daily target
Eg.
Which is very cumbersome. What I would like to be able to do is
create a table on a monthly level for each salesperson and that
PowerBI can "generate/calculate" the daily target in such a way that
I can graph the red line without all the hassle of creating it for
each salesperson manually.
The input would be something like this
+-----------+----------+--------------+--------+----------------+--------------+---------------+
| Date | Month | Salesperson | Branch | Monthly Target | Daily Target | Business days |
+-----------+----------+--------------+--------+----------------+--------------+---------------+
| 1/01/2017 | January | salesperson1 | test | 73529 | 4325 | 17 |
| 1/02/2017 | February | salesperson1 | test | 73529 | 4325 | 20 |
+-----------+----------+--------------+--------+----------------+--------------+---------------+
I have a date dimension table so on my graph I have the date as the x-axis and then the runningorders/runningsales as the y-axis but I would something like a daily runningtarget so that the red line is nicely going with the orders and sales.
I had a look at this pattern but I just cannot figure out how this can generate
a line graph.
https://www.daxpatterns.com/budget-patterns/
So somehow, I guess I would need something which generates this first table with the second table as input. I tried some measures in Dax but none of them give me the cumulative steps for each day. It mostly just shows me the value.
These are the measures I use for the other lines. This works nicely when changing the date filters.
Running sales
RunningTotalSales = CALCULATE(sum(vw_invoice_trn_summary[NetInvoiceValue]),
FILTER(ALLSELECTED(DimTime),DimTime[Date] <= MAX(DimTime[Date])))
Running orders
RunningTotalOrders = CALCULATE(sum(vw_orders_raised[OrderTotal]),FILTER(ALLSELECTED(DimTime),DimTime[Date] <= MAX(DimTime[Date])))
In my current manual solution, the full year though does not work well with the targets line as I am not sure I do it right.
UPDATE
So thinking further about this. It feels like I just need to be able to create a table with a date - daily target - salesperson. based on the monthly targets but not sure how you can do that in power bi. Ideally, you can just add/remove a salesperson and that specific table gets regenerated.
I have two solutions to this. One using DAX and one using the query editor.
DAX Solution:
1. Create a calendar table that has all the dates you need.
If Targets is the table containing your monthly targets, create a new table using a formula like this:
Calendar = CALENDAR(EOMONTH(MIN(Targets[Date]),-1)+1,EOMONTH(MAX(Targets[Date]),0))
2. Create a new table DailyTargets as a cross join of your dates and salespersons.
The CROSSJOIN function creates a row for each date and salesperson combination:
DailyTargets = CROSSJOIN(VALUES('Calendar'[Date]),VALUES(Targets[Salesperson]))
3. Create a calculated column for your daily targets.
I do this by looking up the monthly target and dividing by the number of days in the month:
DailyTarget = DIVIDE(
LOOKUPVALUE(Targets[MonthlyTarget],
Targets[Month], FORMAT(DailyTargets[Date],"mmmm"),
Targets[Salesperson], DailyTargets[Salesperson]),
DAY(EOMONTH(DailyTargets[Date],0)))
Now you have a daily target for each date and each salesperson.
PowerQuery Solution:
1. Create a calendar table that has all the dates you need.
Create a blank query and use the following code:
= List.Dates(List.Min(Targets[Date]),
Duration.Days(Date.EndOfMonth(List.Max(Targets[Date]))
- List.Min(Targets[Date])) + 1,
#duration(1,0,0,0))
2. Convert this list to a table.
Click on "To Table" under the Transform tab and rename the column from "Column1" to "Date".
3. Create a custom column for the month name.
You can use the formulaDate.MonthName([Date]) for this.
4. Merge this query with the Targets table (joining on the Month columns).
5. After merging, expand the Salesperson and MonthlyTarget columns.
6. Create the daily target by dividing the monthly target by the number of days in the month.
You can use the formula [MonthlyTarget]/Date.DaysInMonth([Date]) for this.
The entire query should look like this:
let
Source = List.Dates(List.Min(Targets[Date]), Duration.Days(Date.EndOfMonth(List.Max(Targets[Date])) - List.Min(Targets[Date])) + 1, #duration(1,0,0,0)),
#"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), null, null, ExtraValues.Error),
#"Renamed Columns" = Table.RenameColumns(#"Converted to Table",{{"Column1", "Date"}}),
#"Added Custom" = Table.AddColumn(#"Renamed Columns", "Month", each Date.MonthName([Date])),
#"Merged Queries" = Table.NestedJoin(#"Added Custom",{"Month"},Targets,{"Month"},"Targets",JoinKind.LeftOuter),
#"Expanded Targets" = Table.ExpandTableColumn(#"Merged Queries", "Targets", {"Salesperson", "MonthlyTarget"}, {"Salesperson", "MonthlyTarget"}),
#"Added Custom1" = Table.AddColumn(#"Expanded Targets", "DailyTarget", each [MonthlyTarget]/Date.DaysInMonth([Date]))
in
#"Added Custom1"
Instead of going step by step, you can just paste this into the Advanced Editor if you'd like. (Just be sure you use whatever table name you have instead of Targets.)
I have a much simpler solution for this:
I just need to be able to create a table with a date - daily target - salesperson. based on the monthly targets
Let's say I have a table like this:
Where Month contains the date for the first day of each month. We then add a custom column "Date" using the query editor menu (Add Column > Custom Column). We paste this formula for our new column:
= List.Dates([Month], Date.Day(Date.EndOfMonth([Month])), #duration(1, 0, 0, 0))
Each row of the new column will contain a list of all dates within that row's month. Expand that column by clicking on the button on the top right corner and choosing "Expand to new rows".
Now you have a row for each day, and you can simply add another custom column, "Daily Target", that divides the monthly target by the number of days in each month:
= [Monthly Target]/Date.DaysInMonth([Date])
And your table is ready:
Related
I want to create a new Custom Column in AG grid which will display the calculated value of another column together with the value of the column in the previous row.
We have created lots of calculated columns in AdapTable but i cannot work out how do this.
In our example we have a Price and a Date Column and a Running Price Calculated Column.
For the row where Date is Today, I want to the value in the Running Price column to be 'Price' in this Row plus whatever the Running Price value is in the Row where Date is Yesterday.
And for yesterday's row I want Running Price to include the value for 2 days ago. And so on.
Perhaps this example will help explain:
Price | Date | Running Price
5 | 2 Days Ago | 10
7 | Yesterday | 17
9 | Today | 26
If I can do this without needing to sort AG Grid on the Date column then even better as my users like to do their own sorts and I don't want it to break the running total.
Yes, this can be done fairly easily in AdapTable.
You need to use what it calls an AggregatedScalarQuery.
Assuming that the columns in your grid are called 'Price', and 'MyDate' then the Expression for the 'RunningPrice' Calculated Column will be something like:
CUMUL(SUM([Price]), OVER([MyDate]))
See more at: https://docs.adaptabletools.com/guide/adaptable-ql-expression-aggregation-scalar#cumulative-aggregation
Edit: I should add that you dont need to sort the 'MyDate' column as per your initial message, since OVER will run over the dates in natural sort order. So your users can continue to sort AG Grid how they like without it affecting your Calculated Column.
I have two tables case and party. Both of them are from BigQuery. In the case table, there is a date field in the DATETIME type in BigQuery. I want to plot a chart to show the number of cases per month. It works perfectly when I only use the case table.
However, when I blend the case table with the party table, the aggregation doesn't apply on the date field anymore.
This is how I join the tables.
How do make the aggregation of date & time fields in blends work as normal?
Update
I have tried to create a custom field with TODATE(date, 'RFC_3339', '%Y-%m-%d'), but the aggregation is still not applied to the custom field.
minimal example
Create a.csv in local.
a_id,date
1,2022-05-25T00:00:00
2,2022-05-25T00:00:00
3,2022-06-01T00:00:00
4,2022-06-02T00:00:00
Create b.csv in local.
a_id,b_id
1,1
1,2
2,3
3,4
4,5
4,6
Upload a.csv and b.csv into a Data Studio report.
Blend a.csv and b.csv with inner joining on a_id field. I removed "Record Count" from metrics in both tables and added all fields as dimensions.
Add a "Table" type chart using the blend created in the previous step.
Put date field as the only one dimension and select "Year Month" as the type.
Put a_id field as the only one metrics and select "Count Distinct" as aggregation.
actual result
date (Year Month)
a_id
May 2022
2
Jun 2022
1
Jun 2022
1
expected result
date (Year Month)
a_id
May 2022
2
Jun 2022
2
example report
Here
This is a bug, and it was already reported in Google's DataStudio IssueTracker.
https://issuetracker.google.com/issues/179280180
You probably want to star the issue (Google prioritize issues by the number of affected users).
Also, in the same thread, the reporting user suggests to use the above formula as a workaround.
YearMonthAsDate = DATE(YEAR(date_tran),MONTH(date_tran),1)
It worth a try.
You are changing the Date dimension in the table but in order to aggregate it on a monthly basis but joins the rows on a date base.
The solution is to change the Dimension to Month year inside the blend settings, you can do this just the same way you change a field type inside a table.
all:
I am trying to design a shared worksheet that measures salespeople performance over a period of time. In addition to calculating # of units, sales price, and profit, I am trying to calculate how many new account were sold in the month (ideally, I'd like to be able to change the timeframe so I can calculate larger time periods like quarter, year etc').
In essence, I want to find out if a customer was sold to in the 12 months before the present month, and if not, that I will see the customer number and the salesperson who sold them.
So far, I was able to calculate that by adding three columns that each calculate a part of the process (see screenshot below):
Column H (SoldLastYear) - Shows customers that were sold in the year before this current month: =IF(AND(B2>=(TODAY()-365),B2<(TODAY()-DAY(TODAY())+1)),D2,"")
Column I (SoldNow) - Shows the customers that were sold this month, and if they are NOT found in column H, show "New Cust": =IFNA(IF(B2>TODAY()-DAY(TODAY()),VLOOKUP(D2,H:H,1,FALSE),""),"New Cust")
Column J (NewCust) - If Column I shows "New Cust", show me the customer number: =IF(I2="New Cust",D2,"")
Column K (SalesName) - if Column I shows "New Cust", show me the salesperson name: =IF(I2="New Cust",C2,"")
Does anyone have an idea how I can make this more efficient? Could an array formula work here or will it be stuck in a loop since its referring to other lines in the same column?
Any help would be appreciated!!
EDIT: Here is what Im trying to achieve:
Instead of:
having Column H showing me what was sold in the 12 months before the 1st day of the current month (for today's date: 8/1/19-7/31/20);
Having Column I showing me what was sold in August 2020; and
Column I searching column H to see if that customer was sold in the timeframe specified in Column H
I want to have one column that does all three: One column that flags all sales made for the last 12 months from the beginning of the current month (so, 8/1/19 to 8/27/20), then compares sales made in current month (august) with the sales made before it, and lets me know the first time a customer shows up in current month IF it doesn't appear in the 12 months prior --> finds the new customers after a dormant period of 12 months.
Im really just trying to find a way to make the formula better and less-resource consuming. With a large dataset, the three columns (copied a few times for different timeframes) really slow down Excel...
Here is an example of the end result:
Example of final product
I have a following employee table value as below :
name | cost
john | 1000
john | -1000
john | 5000
when we add the cost column total will be 5000.
I need to print only the 3rd row in BIRT report, since the 1st and 2nd row get cancelled out each other.
I'm stuck at filtering the table for above scenario.
Couldn't you just solve this using SQL like
select name, sum(cost)
from employee
group by name
order by name
?
Or do you just want to exclude two rows if they have exactly the same cost, but with different signs? Note that this is actually something different, take for example the three rows [ john|1, john|2, john|-3 ]? In this case, a pure SQL solution can be achieved using the SQL analytic functions (at least if you are using Oracle).
Elaborate your question. Its not clear if these are columns or rows.
If These are columns:
Create a computed column in your dataset
In Expression builder of that column add/sub values using dataSetRow['col1'] and dataSetRow['col2']
Add only that computed column to your table.
If these are rows
Select rows you don't want to print
Go to properties tab
Find Visibility property and click on it
Check Hide Element option
What is the best way to store occurrences of an event in a database so you can quickly pull reports on it? ie (total number of occurrences, number of occurrences between date range).
right now I have two database tables, one which holds all individual timestamps of the event - so I can query on a date range, and one which holds a total count so I can quickly pull that number for a tally
Table 1:
Event | Total_Count
------+------------
bar | 1
foo | 3
Table 2:
Event | Timestamp
------+----------
bar | 1/1/2010
foo | 1/1/2010
foo | 1/2/2010
foo | 1/2/2010
Is there a better approach to this problem? I'm thinking of converting Table 2, to hold date tallies, it should be more efficient, since my date range queries are only done on whole dates, not a timestamp (1/1/2010 vs 1/1/2010 00:01:12)
ie:
Updated Table 2
Event | Date | Total_Count
------+----------+------------
bar | 1/1/2010 | 1
foo | 1/1/2010 | 1
foo | 1/2/2010 | 2
Perhaps theres an even smarter way to tackle this problem? any ideas?
Your approach seems good. I see table 2 more as a detail table, while table 1 as a summary table. For the most part, you would be doing inserts only to table 2, and inserts and updates on table 1.
The updated table 2 may not give you much additional benefit. However, you should consider it if aggregations by day is most important to you.
You may consider adding more attributes (columns) to the tables. For example, you could add a first_date, and last date to table 1.
I would just have the one table with the timestamp of your event(s). Then your reporting is simply setting up your where clause correctly...
Or am I missing something in your question?
Seems like you don't really have any requirements:
Changing from timestamp to just the date portion is a big deal.
You don't ever want to do a time-of-day analysis?
like what's the best time of day to do maintenance if that stops "foo" from happening.
And you're not worried about size? You say you have millions of records (like that's a lot) and then you extend every single row by an extra column. One column isn't a lot until the row count skyrockets and then you really have to think about each column.
So to get the sum of event for the last 3 days you'd rather do this
SELECT SUM(totcnt) FROM (
SELECT MAX(Total_count) as totcnt from table where date = today and event = 'Foo'
UNION ALL
SELECT MAX(Total_count) from table where date = today-1 and event = 'Foo'
UNION ALL
SELECT MAX(Total_count) from table where date = today-2 and event = 'Foo'
)
Yeah, that looks much easier than>
SELECT COUNT(*) FROM table WHERE DATE BETWEEN today-2 and today and event = 'foo'
And think about the trigger it would take to add a row... get the max for that day and event and add one... every time you insert?
Not sure what kind of server you have but I summed 1 Million rows in 285ms. So... how many millions will you have and how many times do you need to sum them and is each time for the same date range or completely random?