I have a dataset with two tabs, one with monthly goal(target) and another tab with sales and order data. I'm trying to summarize sales data from the other tab into the target tab using several parameters with an Index(Match and SumIfs:
My Attempt:
=SUMIFS(INDEX(OrderBreakdown!$A$2:$T$8048,,MATCH(C2,OrderBreakdown!$G$2:$G$8048)),OrderBreakdown!$I$2:$I$8048,">="&A2,OrderBreakdown!$I$2:$I$8048,"<="&B2)
Order Breakdown is the other sheet, column D in OrderBreakdown sheet is what I want to sum if OrderBreakdown_Category(Col G) = Col C and if OrderBreakdown_Order Date(Col I) >= Start Date(Col A) and if OrderBreakdown_Order Date(Col I) <= End Date(Col A)
My answer should be much more in line with Col D but instead I'm getting $MM
Here's a sample of the dataset I'm pulling from:
dataset I'm pulling from
Ok, I am not sure why your range to sum is from A through T - that is probably where you went wrong. Also, I did not find the index method necessary. This should work for you
=SUMIFS(OrderBreakdown!$D$2:$D$8048,OrderBreakdown!$I$2:$I$8048, ">=" & A2,OrderBreakdown!$I$2:$I$8048, "<=" & B2, OrderBreakdown!$G$2:$G$8048, "<=" & C2)
Here is my sample data Starting on first sheet row 2
1/1/2011 1/30/2011 Office Supplies
Then the orderBreakdown tab starts on column C
Discount Sales Profit Quantity Category sub-category OrderDate
0.5 $45.00 ($26.00) 3 Office Supplies Paper 1/1/11 Eugene Mo Stockholm Sweden North Home Offic 1/5/11 Second Cla: Stockholm 2011-(11 0.1-2011 2011 1/1/2011
0 $854.00 $290.00 7 Furniture BookCases 1/2/2011
0 $854.00 $290.00 7 Furniture BookCases 12/32/2010
Related
I would like to look up a row (an array) based on the DATE value, such that an array of price value (instead of a single return if using VLOOKUP) is returned for a given DATE value. Below is the data
Column A Column B Column C Column D
Row1 DATE Product A Product B Product C
Row2 1/1/2017 1 5 7
Row3 7/1/2017 3 6 5
Row4 13/1/2017 2 8 3
Thank you in advance
So one way to do this would be to make the lookup row a relative value. So assuming that your sample data is on Sheet1 and the list of dates you are looking up against is on Sheet2 Col A with a header. I would first make the lookup range a named range so that Sheet1 Col A thru Col D is named something like "Data". Then in B2 place the below formula and copy it to over to Col D and then all the way down the list of dates.
=vlookup($A2,Data,Column(B1),False)
The $ for A2 allows it to always look at column A even when copying over the formula. The Column(B1) returns a value of 2 but when you copy that formula to the left it will change to Column(c1), Column(d1)... thus changing what column of data you want returned.
I have a table with following columns:
Year, Month, SalesRange, NumOfBuyers, AvgSale. So a sample row would look like:
2015 09 - '1-149.99' - 3 - 89.50
meaning in sep of 2015 there are 3 buyers that placed an order in the value between 1-149.99 and the avg of these 3 buyers' orders is 89.00
I am creating a range column based on the sale column and using the case statement.
For example:
`
CASE
WHEN Sales <= 149.999 THEN '1-149.999'
WHEN Sales > 149.999 AND Sales <= 349.999 THEN '150 - 349.999'
WHEN Sales > 349.999 AND Sales <= 749.999 THEN '350 - 749.999'
WHEN Sales > 749.999 AND Sales <= 999999.999 THEN '750 - 999999.999'
END SalesRange
`
This works great except in the cases where there are no items with, let's say price of $100, in which case the range '1-149.999' never gets displayed.
What I need is that all the ranges are always displayed.
So, from the previous example if there were no buyers whose orders were between 1-149.99 this category would never be displayed and I need it to be displayed with NumOfBuyers = 0 and Sales say equal to NULL.
Does anyone have an idea how to achieve this?
Thanks!!
I have Inventory data that is in the following format:
Column D | Column E | Column F
Pack Qty | Pack Price | Total Qty
This is followed by multiple rows with various numerical values, with the odd blank row.
To calculate the stock value of any particular product/line, I use =F2/D2*E2.
To calculate the total value of stock I tried {=Sum(F:F/D:D*E:E)} but it returns a #Div/0! error.
As mentioned, some rows are blank. Some items have 0 price, others have 0 stock on hand.
I would like to avoid having to total each line in a new column then total that column.
Try this:
{=SUM(IFERROR(F:F/D:D*E:E,0))}
You can simply wrap your division inside IFERROR() and return 0.
{=SUM(IFERROR(F:F/D:D,0)*E:E)}
I'm working on a report that shows transactions grouped by type.
Type Total income
------- --------------
A 575
B 244
C 128
D 45
E 5
F 3
Total 1000
I only want to provide details for transaction types that represent more than 10% of the total income (i.e. A-C). I'm able to do this by applying a filter to the group:
Type Total income
------- --------------
A 575
B 244
C 128
Total 1000
What I want to display is a single row just above the total row that has a total for all the types that have been filtered out (i.e. the sum of D-F):
Type Total income
------- --------------
A 575
B 244
C 128
Other 53
Total 1000
Is this even possible? I've tried using running totals and conditionally hidden rows within the group. I've tried Iif inside Sum. Nothing quite seems to do what I need and I'm butting up against scope issues (e.g. "the value expression has a nested aggregate that specifies a dataset scope").
If anyone can give me any pointers, I'd be really grateful.
EDIT: Should have specified, but at present the dataset actually returns individual transactions:
ID Type Amount
---- ------ --------
1 A 4
2 A 2
3 B 6
4 A 5
5 B 5
The grouping is done using a row group in the tablix.
One solution is to solve that in the SQL source of your dataset instead of inside SSRS:
SELECT
CASE
WHEN CAST([Total income] AS FLOAT) / SUM([Total income]) OVER (PARTITION BY 1) >= 0.10 THEN [Type]
ELSE 'Other'
END AS [Type]
, [Total income]
FROM Source_Table
See also SQL Fiddle
Try to solve this in SQL, see SQL Fiddle.
SELECT I.*
,(
CASE
WHEN I.TotalIncome >= (SELECT Sum(I2.TotalIncome) / 10 FROM Income I2) THEN 10
ELSE 1
END
) AS TotalIncomePercent
FROM Income I
After this, create two sum groups.
SUM(TotalIncome * TotalIncomePercent) / 10
SUM(TotalIncome * TotalIncomePercent)
Second approach may be to use calculated column in SSRS. Try to create a calculated column with above case expression. If it allows you to create it, you may use it in the same way as SQL approach.
1) To show income greater than 10% use row visibility condition like
=iif(reportitems!total_income.value/10<= I.totalincome,true,false)
here reportitems!total_income.value is total of all income textbox value which will be total value of detail group.
and I.totalincome is current field value.
2)add one more row to outside of detail group to achieve other income and use expression as
= reportitems!total_income.value-sum(iif(reportitems!total_income.value/10<= I.totalincome,I.totalincome,nothing))
I have two data sets. FIRST is a list of products and their daily prices from a supplier and SECOND is a list of start and end dates (as well as other important data for analysis). How can I tell Stata to pull the price at the beginning date and then the price at the end date from FIRST into SECOND for the given dates. Please note, if there is no exact matching date I would like it to grab the last date available. For example, if SECOND has the date 1/1/2013 and FIRST has prices on ... 12/30/2012, 12/31/2012, 1/2/2013, ... it would grab the 12/31/2012 price.
I would usually do this with Excel, but I have millions of observations, and it is not feasible.
I have put an example of FIRST and SECOND as well as what the optimal solution would give as an output POST_SECOND
FIRST
Product Price Date
1 3 1/1/2010
1 3 1/3/2010
1 4 1/4/2010
1 2 1/8/2010
2 1 1/1/2010
2 5 2/5/2010
3 7 12/26/2009
3 2 1/1/2010
3 6 4/3/2010
SECOND
Product Start Date End Date
1 1/3/2010 1/4/2010
2 1/1/2010 1/1/2010
3 12/26/2009 4/3/2010
POST_SECOND
Product Start Date End Date Price_Start Price_End
1 1/3/2010 1/4/2010 3 4
2 1/1/2010 1/1/2010 1 1
3 12/26/2009 4/3/2010 7 6
Here's a merge/keep/sort/collapse* solution that relies on using the last date. I altered your example data slightly.
/* Make Fake Data & Convert Dates to Date Format */
clear
input byte Product byte Price str12 str_date
1 3 "1/1/2010"
1 3 "1/3/2010"
1 4 "1/4/2010"
1 2 "1/8/2010"
2 1 "1/1/2010"
2 5 "2/5/2010"
3 7 "12/26/2009"
3 7 "12/28/2009"
3 2 "1/1/2010"
3 6 "4/3/2010"
4 8 "12/30/2012"
4 9 "12/31/2012"
4 10 "1/2/2013"
4 10 "1/3/2013"
end
gen Date = date(str_date,"MDY")
format Date %td
drop str_date
save "First.dta", replace
clear
input byte Product str12 str_Start_Date str12 str_End_Date
1 "1/3/2010" "1/4/2010"
2 "1/1/2010" "1/1/2010"
3 "12/27/2009" "4/3/2010"
4 "1/1/2013" "1/2/2013"
end
gen Start_Date = date(str_Start_Date,"MDY")
gen End_Date = date(str_End_Date,"MDY")
format Start_Date End_Date %td
drop str_*
save "Second.dta", replace
/* Data Transformation */
use "First.dta", clear
merge m:1 Product using "Second.dta", nogen
bys Product: egen ads = min(abs(Start_Date-Date))
bys Product: egen ade = min(abs(End_Date - Date))
keep if (ads==abs(Date - Start_Date) & Date <= Start_Date) | (ade==abs(Date - End_Date) & Date <= End_Date)
sort Product Date
collapse (first) Price_Start = Price (last) Price_End = Price, by(Product Start_Date End_Date)
list, clean noobs
*Some people are reshapers. Others are collapsers. Often both can get the job done, but I think collapse is easier in this case.
In Stata, I've never been able to get something like this to work nicely in one step (something you can do in SAS via a SQL call). In any case, I think you'd be better off creating an intermediate file from FIRST.dta and then merging that 2x on each of your StartDate and EndDate variables in SECOND.dta.
Say you have data for price adjustments from Jan 1, 2010 to Dec 31, 2013 (specified with varied intervals as you have shown above). I assume all the date variables are already in date format in FIRST.dta & SECOND.dta, and that variable names in SECOND do not have spaces in them.
tempfile prod prices
use FIRST.dta, clear
keep Product
duplicates drop
save `prod'
clear
set obs 1096
g Date=date("12-31-2009","MDY")+_n
format date %td
cross using `prod'
merge 1:1 Product Date using FIRST.dta, assert(1 3) nogen
gsort +Product +Date /*this ensures the data are sorted properly for the next step */
replace price=price[_n-1] if price==. & Product==Product[_n-1]
save `prices'
use SECOND.dta, clear
foreach i in Start End {
rename `i'Date Date
merge 1:1 Product Date using `prices', assert(2 3) keep(3) nogen
rename Price Price_`i'
rename Date `i'Date
}
This should work if I understand your data structures correctly, and it should address the issue being discussed in the comments to #Dimitriy's answer. I'm open to critiques on how to make this nicer as its something I've had to do a few times and this is how I usually go about it.