I have three tables:
**OBTable**
Product obquantity obrate obTotalAmmount
Matadoor Pen 100 8 800
Matadoor Pen 1000 4 4000
**PurchaseTable**
pProduct Pquantity pRate SaleRate pTotalAmmount
Matadoor Pen 150 4 5 600
Matadoor Pen 400 8 10 3200
Matadoor Pen 1500 9 10 13500
**SaleTable**
sProduct sQuantity sRate sTotalAmmount
Matadoor Pen 100 10 1000
Matadoor Pen 350 10 3500
Matadoor Pen 1350 10 13500
My query:
SELECT
Product,
SUM(obQuantity) AS obQuantity,
SUM(obTotalAmmount)/SUM(obQuantity) AS obRate,
SUM(obTotalAmmount) AS obTotalAmmount,
pProduct,
SUM(pQuantity) AS pQuantity,
SUM(pTotalAmmount)/SUM(pQuantity) AS pRate,
SUM(pTotalAmmount) AS pTotalAmmount,
sProduct,
SUM(sQuantity) AS sQuantity,
SUM(sTotalAmmount)/SUM(sQuantity) AS sRate,
SUM(sTotalAmmount) as sTotalAmmount,
Sum(obQuantity) +SUM(pquantity) -Sum(squantity) as obpsQTY,
(Sum(obTotalAmmount)+Sum(pTotalAmmount)-sum(sTotalAmmount))/(Sum(obQuantity)+SUM(pQuantity)-Sum(sQuantity)) as obpsrate ,
(Sum(obTotalAmmount)+Sum(pTotalAmmount))-Sum(sTotalAmmount) as obpstotal
from OBTable
left join
PurchaseTable on OBTable.Product=PurchaseTable.pProduct
left join
Saletable on PurchaseTable.pProduct=SaleTable.sProduct
Group BY OBTable.Product,PurchaseTable.pProduct,Saletable.sProduct
It's executed answer is not correct. Plz help me and give tips to solve it.
You can try this code:
Select Product,
Sum(obQuantity) As obQuantity,
(SUM(obTotalAmmount)/Sum(obQuantity)) As obRate,
SUM(obTotalAmmount) as obTotalAmmount,
pQuantity,pRate,pTotalAmmount,
sQuantity ,sRate,sTotalAmmount,
(Sum(obQuantity) +pquantity) -squantity as obpsQTY,
(((SUM(obTotalAmmount)/Sum(obQuantity)))+pRate)/2 as obpsrate ,
((((SUM(obTotalAmmount)/Sum(obQuantity)))+pRate)/2)*((Sum(obQuantity) +pquantity) -squantity) as obpstotal
from OBTable
left join (
Select pProduct,Sum(pQuantity) As pQuantity ,(Sum(pTotalAmmount)/Sum(pQuantity)) As pRate,Sum(pTotalAmmount) As pTotalAmmount
from PurchaseTable
Group by PurchaseTable.pProduct
)
PurchaseTable on OBTable.Product=PurchaseTable.pProduct
left join
(
Select sProduct,Sum(sQuantity) As sQuantity ,(Sum(sTotalAmmount)/Sum(sQuantity)) As sRate,Sum(sTotalAmmount) As sTotalAmmount
from SaleTable
Group by SaleTable.sProduct
) Saletable on PurchaseTable.pProduct=SaleTable.sProduct
Group by OBTable.Product,PurchaseTable.pProduct,Saletable.sProduct,PurchaseTable.pQuantity,PurchaseTable.pRate,PurchaseTable.pTotalAmmount,Saletable.sQuantity,Saletable.sRate,Saletable.sTotalAmmount
Related
On a sheet named, "Performance," I have data concerning stock trades in a row like so:
A B C D E F G H I J
1 TICKER TRADE OPEN DATE TRADE CLOSED DATE SHARES AVG BUY INVESTMENT AVG SALE PROCEEDS PROFIT/LOSS ROIC:
2 ABC 01/05/22 03/31/22 107 $14.22 -$1,521.54 $15.00 $1,605.00 $83.46 5.49%
3 BCA 01/05/22 03/31/22 344 $14.52 -$4,994.88 $15.00 $5,160.00 $165.12 3.31%
4 CAB 01/05/22 03/31/22 526 $12.55 -$6,601.30 $13.00 $6,838.00 $236.70 3.59%
... and so forth ...
Within the same workbook but on a separate sheet named, "Contributions/Withdrawals," I have a list of contributions and withdrawals like so:
A B
1 DATE AMOUNT
2 01/05/22 $700.00
3 02/05/22 $700.00
4 03/05/22 $400.00
5 03/15/22 -$7,000.00
... and so forth ...
I need to convert the first table of trade transactions into a vertical column format exactly like what is in the Contributions/Withdrawals table. (Note that each trade transaction actually represents two transactions, one for opening with its own date, and one for closing with its date.) Finally, I need to stack both tables of transactions in date order to make a combined chronological list of transactions so that I can run an XIRR formula on it.
The resulting table on a sheet named, "Cash Flows," needs to look like this:
A B
1 DATE AMOUNT
2 01/05/22 -$1,521.54
3 01/05/22 -$4,994.88
4 01/05/22 -$6,601.30
5 01/05/22 $700.00
6 02/05/22 $700.00
7 03/05/22 $700.00
8 03/10/22 $400.00
9 03/15/22 -$7000.00
10 03/31/22 $1,605.00
11 03/31/22 $5,160.00
12 03/31/22 $6,838.00
Using the following in cell A2 and B2...
A2 =SORT({Performance!$B$2:$B;Performance!$C$2:$C;'Contributions/Withdrawals'!$A$2:$A})
B2 =SORT({Performance!$F$2:$F;Performance!$H$2:$H;'Contributions/Withdrawals'!$B$2:$B})
...almost gets me there, but the transactions are not lining up with the correct dates. Google Sheets is ordering the amounts from smallest to largest. What I end up with is this:
A B
1 DATE AMOUNT
2 01/05/22 -$7,000.00
3 01/05/22 -$6,602.72
4 01/05/22 -$6,602.39
5 01/05/22 -$6,601.30
6 01/05/22 -$6,596.40
7 01/05/22 -$6,587.10
8 01/05/22 -$4,994.88
9 01/05/22 -$3,315.26
10 01/05/22 -$3,284.91
11 01/05/22 -$1,521.54
12 02/05/22 $400.00
13 03/05/22 $700.00
14 03/10/22 $700.00
15 03/15/22 $700.00
16 03/31/22 $1,605.00
17 03/31/22 $3.249.00
18 03/31/22 $3,731.00
19 03/31/22 $5,160.00
20 03/31/22 $6,348.00
21 03/31/22 $6,532.00
22 03/31/22 $6,786.00
23 03/31/22 $6,838.00
Any help would be appreciated. Thanks!
You are very close indeed! You should join both ranges in order to sort them by the first column:
=SORT({Performance!$B$2:$B;Performance!$C$2:$C;'Contributions/Withdrawals'!$A$2:$A,Performance!$F$2:$F;Performance!$H$2:$H;'Contributions/Withdrawals'!$B$2:$B})
(You may need to change that only comma to a inverted slash if you have another locale settings)
Table 1:
Position
Team
1
MCI
2
LIV
3
MAN
4
CHE
5
LEI
6
AST
7
BOU
8
BRI
9
NEW
10
TOT
Table 2
Position
Team
1
LIV
2
MAN
3
MCI
4
CHE
5
AST
6
LEI
7
BOU
8
TOT
9
BRI
10
NEW
Output I'm looking for is
Position difference = 10 as that is the total of the positional difference. How can I do this in excel/google sheets? So the positional difference is always a positive even if it goes up or down. Think of it as a league table.
Table 2 New (using formula to find positional difference):
Position
Team
Positional Difference
1
LIV
1
2
MAN
1
3
MCI
2
4
CHE
0
5
AST
1
6
LEI
1
7
BOU
0
8
TOT
2
9
BRI
1
10
NEW
1
Try this:
=IFNA(ABS(INDEX(A:B,MATCH(E2,B:B,0),1)-D2),"-")
Assuming that table 1 is at columns A:B:
Hello all Sheet users out there.
I have a sheet with a list of resources with their production and usage being calculated on the left side and the overall prod/use being monitored on the right side.
A B C D | E F G H
1 Input In Output Out | Resource totIn totOut effective
2 Iron 20 FeIngot 30 | Iron 30 =SUMIF(...) =totIn-totOut
3 Copper 20 CuIngot 20 | Copper 25 =SUMIF(...) =totIn-totOut
4 Stone 10 Gravel 50 | CuIngot =SUMIF(...) =SUMIF(...) =totIn-totOut
5 FeIngot 10 FePlate 5 | FeIngot =SUMIF(...) =SUMIF(...) =totIn-totOut
6 CuIngot 25 Wire 75 | Stone 45 =SUMIF(...) =totIn-totOut
7 CuIngot 10 Cable 20 | Gravel =SUMIF(...) =SUMIF(...) =totIn-totOut
The actual sheet would look more like this:
A B C D | E F G H
1 Input In Output Out | Resource totIn totOut effective
2 Iron 20 FeIngot 30 | Iron 30 20 10
3 Copper 20 CuIngot 20 | Copper 25 20 5
4 Stone 10 Gravel 50 | CuIngot 20 35 -15
5 FeIngot 10 FePlate 5 | FeIngot 30 10 20
6 CuIngot 25 Wire 75 | Stone 45 10 35
7 CuIngot 10 Cable 20 | Gravel 50 0 50
On the left side, I want to mark all cells in column "In" red that have a negative effective production calculated on the right side. I thought about using the conditional formatting, looping through every text cell in the "Resource" column to find the one that equals the "Input" of the same row the cell I want to check is in and then check if the "effective" value of the "Resource" I found is less than 0. The problem is that I don't know how to loop through the values and store the matching row to check if the H value is negative.
Example 1: B6 is checked. A6 needs to be compared to every cell in E2:E and when there is a match, in this case E4, check if H4 is negative. It is, so there is formatting applied.
Example 2: B3 is checked. A3 needs to be compared to every cell in E2:E and when there is a match, in this case E3, check if H3 is negative. It is not, so there is no formatting applied.
Is there any way that I can apply this formatting in the conditional formatting tool?
Keep in mind that my sheet is much more complex than these examples and it has about 120 resources that can't all be moved in order with the left side because multiple rows can use the same resource as input or output.
Thank you in advance for every ounce of your help.
try this formula =VLOOKUP($A1,$E:$H,4,false)<0 in conditional formatting
I have been given matrices filled with alphanumerical values excluding lower case letters like so:
XX11X1X
XX88X8X
Y000YYY
ZZZZ789
ABABABC
and have been tasked with counting the repetitions in each row and then tallying up a score depending on the ranking of the character being repeated. I used {⍺ (≢⍵)}⌸¨ ↓ m to help me. For the example above I would get something like this:
X 4 X 4 Y 4 Z 4 A 3
1 3 8 3 0 3 7 1 B 3
8 1 C 1
9 1
This is great but now I need to do a function that would be able to multiply the numbers with each letter. I can access the first matrix with ⊃ but then I am completely lost on how to access the other ones. I can simply write ⊃w[2] and ⊃w[3] and so forth but I need a way to change every matrix at the same time in one function. For this example, the array of the ranking is as follow: ZYXWVUTSRQPONMLKJIHGFEDCBA9876543210 so for the first array XX11X1X
which corresponds to:
X 4
1 3
So the X is 3rd in the array so it corresponds to a 3 and 1 is 35th so it's a 35. The final scoring would be something like (3×104)+(35×103). My biggest problem is not necessarily the scoring part but being able to access each matrix individually in one function. So for this nested array:
X 4 X 4 Y 4 Z 4 A 3
1 3 8 3 0 3 7 1 B 3
8 1 C 1
9 1
if I do arr[1] it gives me the scalar
X 4
1 3
and ⍴ arr[1] gives me nothing confirming it so I can do ⊃arr[1] to get the matrix itself and have access to each column individually. This is where I'm stuck. I'm trying to write a function to be able to do the math for each matrix and then saving those results to an array. I can easily do the math for the first matrix but I can't do it for all of them. I might have made a mistake by making using {⍺ (≢⍵)}⌸¨ ↓ m to get those matrices. Thanks.
Using your example arrangement:
⎕ ← arranged ← ⌽ ⎕D , ⎕A
ZYXWVUTSRQPONMLKJIHGFEDCBA9876543210
So now, we can get the index values:
1 ⌷ m
XX11X1X
∪ 1 ⌷ m
X1
arranged ⍳ ∪ 1 ⌷ m
3 35
While you could compute the intermediary step first, it is much simpler to include most of the final formula in in Key's operand:
{ ( arranged ⍳ ⍺ ) × 10 * ≢⍵ }⌸¨ ↓m
┌───────────┬───────────┬───────────┬─────────────────┬───────────────┐
│30000 35000│30000 28000│20000 36000│10000 290 280 270│26000 25000 240│
└───────────┴───────────┴───────────┴─────────────────┴───────────────┘
Now we just need to sum each:
+/¨ { ( arranged ⍳ ⍺ ) × 10 * ≢⍵ }⌸¨ ↓m
65000 58000 56000 10840 51240
In fact, we can combine the summation with the application of Key to avoid a double loop:
{ +/ { ( arranged ⍳ ⍺ ) × 10 * ≢⍵ }⌸ ⍵}¨ ↓m
65000 58000 56000 10840 51240
For completeness, here is a way to use the intermediary result. Let's start by working on just the first matrix (you can get the second one with 2⊃ instead of ⊃ ― for details, see Problems when trying to use arrays in APL. What have I missed?):
⊃{⍺ (≢⍵)}⌸¨ ↓m
X 4
1 3
We can insert a function between the left column elements and the right column elements with reduction:
{⍺ 'foo' ⍵}/ ⊃{⍺ (≢⍵)}⌸¨ ↓m
┌─────────┬─────────┐
│┌─┬───┬─┐│┌─┬───┬─┐│
││X│foo│4│││1│foo│3││
│└─┴───┴─┘│└─┴───┴─┘│
└─────────┴─────────┘
So now we simply have to modify the placeholder function with one that looks up the left argument in the arranged items, and multiplies by ten to the power of the right argument:
{ ( arranged ⍳ ⍺ ) × 10 * ⍵ }/ ⊃{⍺ (≢⍵)}⌸¨ ↓m
30000 35000
Instead of applying this to only the first matrix, we apply it to each matrix:
{ ( arranged ⍳ ⍺ ) × 10 * ⍵ }/¨ {⍺ (≢⍵)}⌸¨ ↓m
┌───────────┬───────────┬───────────┬─────────────────┬───────────────┐
│30000 35000│30000 28000│20000 36000│10000 290 280 270│26000 25000 240│
└───────────┴───────────┴───────────┴─────────────────┴───────────────┘
Now we just need to sum each:
+/¨ { ( arranged ⍳ ⍺ ) × 10 * ⍵ }/¨ {⍺ (≢⍵)}⌸¨ ↓m
65000 58000 56000 10840 51240
However, this is a much more circuitous approach, and is only provided here for reference.
I have massaged a dataframe so it looks like this:
123
456
789
0AB
CDE
FGH
...
,,,
I would like to transform it, so it looks like this:
123789CDE...
4560ABFGH,,,
The pattern is this:
123 789 CDE ...
456 0AB FGH ,,,
That is, I take two rows and concatenate the next two rows, etc, so I get a wide dataframe.
But my real dataframe is not three columns, it is maybe 50 columns, and maybe 100,000 rows, so my dataframe is 100,000 x 50 big. I want to take 100 rows, and concatenate the next 100 rows, etc so I get a wide dataframe with dimension 100 x (50 * 100,000/100) = 100 x 50,000.
Can Pandas do this? My aim is to do some calculations on each of these 100 rows. Or is hierarchical indexing better?
shell [33]>>> df
[33]>>>
0
0 123
1 456
2 789
3 0AB
4 CDE
5 FGH
6 ...
7 ,,,
shell [34]>>> pd.DataFrame(df.values.reshape(4, 2)).sum()
[34]>>>
0 123789CDE...
1 4560ABFGH,,,
dtype: object
Another approach is using groupby.
shell [35]>>> df['group'] = 0
shell [36]>>> df[1::2]['group'] = 1
shell [37]>>> grouped = df.groupby('group')
shell [38]>>> grouped.sum()
[38]>>>
0
group
0 123789CDE...
1 4560ABFGH,,,
Maybe worth studying not to create a new frame and instead work directly on the groups? Certainly for multiple columns and huge numnber of rows.
shell [39]>>> for key, group in grouped:
print key
print group
....:
0
0 group
0 123 0
2 789 0
4 CDE 0
6 ... 0
1
0 group
1 456 1
3 0AB 1
5 FGH 1
7 ,,, 1