First off, I admit that I am not sure whether what I am trying to achieve is possible (or even logical). Still I am putting forth this query (and if nothing else, at least be told that I need to redesign my table structure / business logic).
In a table (myValueTable) I have the following records:
Item
article
from_date
to_date
myStock
1
Paper
01/04/2021
31/12/9999
100
2
Tray
12/04/2021
31/12/9999
12
3
Paper
28/04/2021
31/12/9999
150
4
Paper
06/05/2021
31/12/9999
130
As part of the underlying process, I am to find out the value (of field myStock) as on a particular date, say 30/04/2021 (assuming no inward / outward stock movement in the interim).
To that end, I have the following values:
varRefDate = 30/04/2021
varArticle = "Paper"
And my query goes something like this:
get_value = myValueTable.objects.filter(from_date__lte=varRefDate, to_date__gte=varRefDate).get(article=varArticle).myStock
which should translate to:
get_value = SELECT myStock FROM myValueTable WHERE varRefDate BETWEEN from_date AND to_date
But with this I am coming up with more than one result (actually THREE!).
How do I restrict the query result to get ONLY the 3rd instance i.e. the one with value "150" (for article = "paper")?
NOTE: The upper limit of date range (to_date) is being kept constant at 31/12/9999.
Edit
Solved it. In a round about manner. Instead of .get, resorted to generating values_list with fields from_date and myStock. Using the count of objects returned; appended a list with date difference between from_date and the ref date (which is 30/04/2021) and the value of field myStock, sorted (ascending) the generated list. The first tuple in the sorted list will have the least date difference and the corresponding myStock value and that will be the value I am searching for. Tested and works.
Related
I've been trying to do a report about the quantity of breakdonws of products in our company. The problem is that the QUERY function is operating as normal, but the sorting order is well - a bit strange.
The data I'm trying to sort are as follows (quantities are blacked out since I cannot share those informations):
Raw data
First column - name of the product, second, it's EAN code, third, breakdown rate for last year, last column - average breakdown rate. "b/d" means "brak danych" or no data.
What I want to achieve is to get the end table with values sorted by average breakdown rate.
My query is as follows:
=query(Robocze!A2:D;"select A where A is not null and NOT D contains 'b/d' order by D desc")
Final result
As You can see, we have descending order, but there are strange artifacts - like the 33.33% after 4,00% and before 3,92%.
Why is that!?
try:
=INDEX(LAMBDA(x; SORT(x; INDEX(x;; 4)*1; 0))
(QUERY(Robocze!A2:D; "where A is not null and NOT D contains 'b/d'"; 0));; 4)
I want to count the occurrences of values in a column. In my case the value I want to count is TRUE().
Lets say my table is called Table and has two columns:
boolean value
TRUE() A
FALSE() B
TRUE() A
TRUE() B
All solutions I found so far are like this:
count_true = COUNTROWS(FILTER(Table, Table[boolean] = TRUE()))
The problem is that I still want the visual (card), that displays the measure, to consider the filters (coming from the slicers) to reduce the table. So if I have a slicer that is set to value = A, the card with the count_true measure should show 2 and not 3.
As far as I understand the FILTER function always overwrites the visuals filter context.
To further explain my intent: At an earlier point the TRUE/FALSE column had the values 1/0 and I could achieve my goal by just using the SUM function that does not specify a filter context and just acts within the visuals filter context.
I think the DAX you gave should work as long as it's a measure, not a calculated column. (Calculated columns cannot read filter context from the report.)
When evaluating the measure,
count_true = COUNTROWS ( FILTER ( Table, Table[boolean] = TRUE() ) )
the first argument inside FILTER is not necessarily the full table but that table already filtered by the local filter context (including report/page/visual filters along with slicer selections and local context from e.g. rows/column a matrix visual).
So if you select Value = "A" via slicer, then the table in FILTER is already filtered to only include "A" values.
I do not know for sure if this will fix your problem but it is more efficient dax in my opinion:
count_true = CALCULATE(COUNTROWS(Table), Table[boolean])
If you still have the issue after changing your measure to use this format, you may have an underlying issue with the model. There is also the function KEEPFILTERS that may apply here but I think using KEEPFILTERS is overcomplicating your case.
I am trying to calculate month over month difference but it makes data negative.
I created a measure, but it makes source data negative.
CALCULATE (
COUNTA ( SOURCE_DATA[COLUMN] ),
FILTER ( SOURCE_DATA, SOURCE_DATA[YYYYMM] = "201906" )
)
- (
CALCULATE (
COUNTA ( SOURCE_DATA[COLUMN] ),
FILTER ( SOURCE_DATA, SOURCE_DATA[YYYYMM] = "201905" )
)
)
The outcome is correct, but it changes data in previous month to negative.
This is due to the filter context and the way you've written the measure.
Look at the visual table. For the field corresponding to Column = 201905 and row = GA you get -16 813. This is because the context of the visual table tells CALCULATE to COUNTA(SOURCE_DATA[Column]) only when MtM = GA and Columns = 201905. However, adding the FILTER you also tell CALCULATE to keep these criteria AND also make sure that SOURCE_DATA[Column] = 201906 in the first calculate and 201905 in the second one.
This results in CALCULATE looking for rows where Column is both 201905 and 201906 at the same time. Or in other words you generate a venn diagram with no overlapping fields. Therefore the first calculate evaluates to 0 and the second to 16 813, so that the measure is actually evaluating 0-16813 = -16 813.
Since you didn't post any description of your data model I can inly guess what it looks like. However, since you're filtering on the SOURCE_DATA table I guess you don't use a Calendar table. This you should do! Have a calendar with a 1:* (1-to-many) relationship with the SOURCE_DATA and do filtering on the calendar. In addition you can have dynamically calculated day/week/month/year offsets so that you can create measures which don't have to be updated when there's a new month.
I think this video can be helpful: sqlbi videolecture
Also, have a look at this article: sqlbi filter in calculate
I am trying to use power pivot to analyze a stock portfolio at any point in time.
The data model is:
transactions table with buy and sell transactions
historical_prices table with the closing price of each stock
security_lookup table with the symbol and other information about the stock (whether it’s a mutual fund, industry, large cap, etc.).
One to many relationships link the symbol column in security_lookup to the transactions and historical_prices tables.
I am able to get the cost basis to work correctly by doing sumx(transactions, quantity*price). However, I’m not able to get the current value of my holdings. I have a measure called “Current Price” which finds the most recent closing price by
Current Price :=
CALCULATE (
LASTNONBLANK ( Historical_prices[close], min[close] ),
FILTER (
Historical_Prices,
Historical_prices[date] = LASTDATE ( historical_prices[date] )
)
)
However, when I try to find the current value of a security by using
Current Value = sumx(transactions,transactions[quantity]*[Current Price])
the total is not accurate. I'd appreciate suggestions on a way to find the current value of a position. Preferably using sumx or an iterator function so that the subtotals are accurate.
The problem with your Current Value measure is that you are evaluating [Current Price] within the row context of the transactions table (since SUMX is an iterator), so it's only seeing the date associated with that row instead of the last date. Or more precisely, that row's date is the last date in the measure's filter context.
The simplest solution is probably to calculate the Current Price outside of the iterator using a variable and then pass that constant in so you don't have to worry about row and filter contexts.
Current Value =
VAR CurrentPrice = [Current Price]
RETURN SUMX(transactions, transactions[quantity] * CurrentPrice)
I am having trouble to understand why a for loop construction does not work. I am not really used to for loops so I apologize if I am missing something basic. Anyhow, I appreciate any piece of advice you might have.
I am using a party level dataset from the parlgov project. I am trying to create a variable which captures how many times a party has been in government before the current observation. Time is important, the counter should be zero if a party has not been in government before, even if after the observation period it entered government multiple times. Parties are nested in countries and in cabinet dates.
The code is as follows:
use "http://eborbath.github.io/stackoverflow/loop.dta", clear //to get the data
if this does not work, I also uploaded in a csv format, try:
import delimited "http://eborbath.github.io/stackoverflow/loop.csv", bindquote(strict) encoding(UTF-8) clear
The loop should go through each country-specific cabinet date, identify the previous observation and check if the party has already been in government. This is how far I have got:
gen date2=cab_date
gen gov_counter=0
levelsof country, local(countries) // to get to the unique values in countries
foreach c of local countries{
preserve // I think I need this to "re-map" the unique cabinet dates in each country
keep if country==`c'
levelsof cab_date, local(dates) // to get to the unique cabinet dates in individual countries
restore
foreach i of local dates {
egen min_date=min(date2) // this is to identify the previous cabinet date
sort country party_id date2
bysort country party_id: replace gov_counter=gov_counter+1 if date2==min_date & cabinet_party[_n-1]==1 // this should be the counter
bysort country: replace date2=. if date2==min_date // this is to drop the observation which was counted
drop min_date //before I restart the nested loop, so that it again gets to the minimum value in `dates'
}
}
The code works without an error, but it does not do the job. Evidently there's a mistake somewhere, I am just not sure where.
BTW, it's a specific application of a problem I super often encounter: how do you count frequencies of distinct values in a multilevel data structure? This is slightly more specific, to the extent that "time matters", and it should not just sum all encounters. Let me know if you have an easier solution for this.
Thanks!
The problem with your loop is that it does not keep the replaced gov_counter after the loop. However, there is a much easier solution I'd recommend:
sort country party_id cab_date
by country party_id: gen gov_counter=sum(cabinet_party[_n-1])
This sorts the data into groups and then creates a sum by group, always up to (but not including) the current observation.
I would start here. I have stripped the comments so that we can look at the code. I have made some tiny cosmetic alterations.
foreach i of local dates {
egen min_date = min(date2)
sort country party_id date2
bysort country party_id: replace gov_counter=gov_counter+1 ///
if date2 == min_date & cabinet_party[_n-1] == 1
bysort country: replace date2 = . if date2 == min_date
drop min_date
}
This loop includes no reference to the loop index i defined in the foreach statement. So, the code is the same and completely unaffected by the loop index. The variable min_date is just a constant for the dataset and the same each time around the loop. What does depend on how many times the loop is executed is how many times the counter is incremented.
The fallacy here appears to be a false analogy with constructs in other software, in which a loop automatically spawns separate calculations for different values of a loop index.
It's not illegal for loop contents never to refer to the loop index, as is easy to see
forval j = 1/3 {
di "Hurray"
}
produces
Hurray
Hurray
Hurray
But if you want different calculations for different values of the loop index, that has to be explicit.