I have the following table (4 users, 7 properties, 4 mortgages)
How can I calculate the AVERAGE and MEDIAN of distinct properties per a user?
For example I want to get the following results:
AVG = (2+1+1+3)/4 = 1.75
MEDIAN ... 1/1/2/3 = 1.5
See Picture
I was trying to have smth like the below but it doesn’t work (It says error in calculations)
avgOver
(
sum(distinct_count({Property_id})), [User_id]
)
Related
I'm trying to understand why below query is taking too long to retrieve results. I have mocked up the values used but the below query is right and is returning 40 records (a node has 8 diff values and z node has 5 diff values so total 40 combinations). It's taking 2.5 min to return those 40 records. Please let me know what the issue is here. I'm suspecting this to be Neo4j version and infrastructure we're using right now in production.
After the below query we have algo.kShortestPaths.stream so the whole thing together is taking more than 5 min. What do you suggest? Is there no other way where we can handle such combinations (a and z node combinations > 40) within 5 min?
Infrastructure details: Neo4j 3.5 community edition
2 separate datacenters, sync job - 64GB mem 16GB CPU 4 cores
Cypher Query:
MATCH (s:SiteNode {siteName: 'siteName1'})-[rl:CONNECTED_TO]-(a:EquipmentNode)
WHERE a.locationClli = s.siteName AND toUpper(a.networkType) = 'networkType1' AND NOT (toUpper(a.equipmentTid) CONTAINS 'TEST')
WITH a.equipmentTid AS tid_A
MATCH pp = (a:EquipmentNode)-[rel:CONNECTED_TO]-(a1:EquipmentNode)
WHERE a.equipmentTid = tid_A AND ALL( t IN relationships(pp)
WHERE t.type IN ['Type1'] AND (t.totalChannels > 0 AND t.totalChannelsUsed < t.totalChannels) AND t.networkId IN ['networkId1'] AND t.status IN ['status1', 'status2'] )
WITH a
MATCH (d:SiteNode {siteName: 'siteName2'})-[rl:CONNECTED_TO]-(z:EquipmentNode)
WHERE z.locationClli = d.siteName AND toUpper(z.networkType) = 'networkType2' AND NOT (toUpper(z.equipmentTid) CONTAINS 'TEST')
WITH z.equipmentTid AS tid_Z, a
MATCH pp = (z:EquipmentNode)-[rel:CONNECTED_TO]-(z1:EquipmentNode)
WHERE z.equipmentTid=tid_Z AND ALL(t IN relationships(pp)
WHERE t.type IN ['Type2'] AND (t.totalChannels > 0 AND t.totalChannelsUsed < t.totalChannels) AND t.networkId IN ['networkId2'] AND t.status IN ['status1', 'status2'])
WITH DISTINCT z, a
return a.equipmentTid, z.equipmentTid
This query was built to handle small combinations upto 4 total a and z node combinations but today we might have combinations greater than 10 or 40 or 100 so this is timing out. I'm not sure if there's a better way to write the query to improve performance assuming the community edition is good enough for our case.
In my cube, I have several measures at the day grain that I'd like to sum at the day grain but average (or take latest) at the month grain or year grain.
Example:
We have a Fact table with Date and number of active subscribers in that day (aka PMC). This is snapshotted per day.
dt
SubscriberCnt
1/1/22
50
1/2/22
55
This works great at the day level. At the month level, we don't want to sum these two values (count = 105) because it doesn't make sense and not accurate.
when someone is looking at month grain, it should look like this - take the latest for the month. (we may change this to do an average instead, management is still deciding)
option 1 - Take latest
Month-Dt
Subscribers
Jan-2022
55
Feb-2022
-
option 2 - Take aveage
Month-Dt
Subscribers
Jan-2022
52
Feb-2022
-
I've not been able to find the right search terms for this but this seems like a common problem.
I added some sample data at the end of a month for testing:
dt
SubscriberCnt
12/30/21
46
12/31/21
48
This formula uses LASTNONBLANKVALUE, which sorts by the first column and provides the latest value that is not blank:
Monthly Subscriber Count = LASTNONBLANKVALUE( 'Table'[dt], SUM('Table'[SubscriberCnt]) )
If you do an AVERAGE, a simple AVERAGE formula will work. If you want an average just for the current month, then try this:
Current Subscriber Count =
VAR _EOM = CLOSINGBALANCEMONTH( SUM('Table'[SubscriberCnt]), DateDim[Date] )
RETURN IF(_EOM <> 0, _EOM, AVERAGE('Table'[SubscriberCnt]) )
But the total row will be misleading, so I would add this so the total row is the latest number:
Current Subscriber Count =
VAR _EOM = CLOSINGBALANCEMONTH( SUM('Table'[SubscriberCnt]), DateDim[Date] ) //Get the number on the last day of the month
VAR _TOT = NOT HASONEVALUE(DateDim[MonthNo]) // Check if this is a total row (more than one month value)
RETURN IF(_TOT, [Monthly Subscriber Count], // For total rows, use the latest nonblank value
IF(_EOM <> 0, _EOM, AVERAGE('Table'[SubscriberCnt]) ) // For month rows, use final day if available, else use the average
)
I have a list of products and would like to get a 50 day simple moving average of its volume using Power Query (M).
The table is sorted by product name and date. I add a custom column and applied the code below.
if [date] >= #date(2018,1,29)
then List.Average(List.Range(Source[Volume],[Volume]-1,-50))
else ""
Since it is already sorted by date and name, an if statement was applied with a date as criteria/filter. However, an error occurs that says
'Volume' column not found in the table.
I expect to have an added column in the power query with volume 50 day moving average per product. the calculation to be done if date is greater than or equal Jan 29, 2018.
We don't know what your columns are, but assuming you have [product], [date] and [volume] in Source, this would average the last 50 days of [volume] for the identical [product] based on each [date], and place in a new column
AvgAmountAdded = Table.AddColumn(Source, "AverageAmount", (i) => List.Average(Table.SelectRows(Source, each ([product] = i[product] and [date]<=i[date] and [date]>=Date.AddDays(i[date],-50)))[volume]), type number)
Finally! found a solution.
First, apply Index by product see this post for further details
Then index again without criteria (index all rows)
Then, apply below code
= Table.AddColumn(#"Previous Step", "Volume SMA(50)", each if [Index_byProduct] >= 50 then List.Average(List.Range(#"Previous Step"[Volume], ([Index_All]-50),50)) else 0),
For large dataset, Table.Buffer function is recommended after index-expand step to improve PQ calculation speed
I have database where i am calculating the shipping cost. The logic of shipping cost is such way that it is calculated every 500gm. I have price list according to different weight but when i am using calculation taking the weight from user for example 1.4 i am unable to get it to next calculative weight of 1.5 , .7 to 1.0 , 1.7 to 2.0 how to achieve this?
Try this (substitute myNumber to get a different result):
Let (
[
myNumber=2.6;
myNumberInt = INT(myNumber);
myNumberFr = myNumber - myNumberInt;
myNumberFr = Case ( myNumberFr =0;0;myNumberFr >0.5 ; 1;0.5 );
result = myNumberInt + myNumberFr
]
;
result
)
You can wrap it in a custom function, in case you need to change it later throughout the system.
I am sure there is a better mathematical formula, but this should get you started
The Problem is fixed.
I have price list according to weight slab in different table.
I used the Country code with Zone id to track prices for particular weight slab prices provided by the courier company.
The price list for e.g. is in such way :-
Zone 1 .5Kg 100Yuan 1.0Kg 120 yuan etc etc , there goes till 20Kg in some case at max.
so when i input the weight in weight field for e.g. 13.5kg i use this weight / .5 which gives me a value 27 , the reason i use to divide the weight with .5 is for example if i input the weight to 13.8 kg i get 27.6 there upon i embed this in ceiling function in calculation field which gives me value of 28 which i can use to calculate the next price slab in the price list which is for every 500Gms +- .
Once i get this done i use this in script which does the job of going to particular layout to search the zone and the prices and retrieving those data to original layout to show the desired result.
Regards,
Soni
I have a report with multiple datasets. In one of them I need to reference the group total from another dataset. It looks like this:
Tablix1:
Region1 Total Age1 Age2
a 7 5 2
b 12 6 6
c 20 12 8
Total 39 23 16
Tablix2:
Region2 Value %
a 4 57.14%
b 6 50.00%
c 5 25.00%
The values in the "%" column of Tablix2 come from formula: %a = Tablix2 Value a / Tablix1 Total a.
My current expression in % column of Tablix2 looks like:
=CountDistinct(Fields!ID.Value, "Region2")/CountDistinct(Fields!CONSTITUENT_ID.Value, "Tablix1")
but what I get is the percentage calculated of the Total row of Tablix1 and not each Region of Tablix1.
The Lookup function would work for this. It's similar to a vlookup in Excel. It would look something like this:
=Lookup(Fields!Region1.Value, Fields!Region2.Value, Fields!ID.Value, "Region2")
This would pull the corresponding value from Region 2 into Tablix 1. You can just switch it around if you want it in the other table.