I am new to Spotfire so I hope that I ask this question correctly.
My table contains Corp_ID, Date and Flagged columns. The flagged column is either "1" or "0" based on if that Corp_ID had production on that date.
I need a custom expression that will return "0" if the flagged column is "0", BUT if the flagged column is "1" then I need it to return how many consecutive "1"s are in that string for that Corp_ID.
Corp_ID Date Flagged New Column
101 1/1/2016 1 1
101 1/2/2016 0 0
101 1/3/2016 1 4
101 1/4/2016 1 4
101 1/5/2016 1 4
101 1/6/2016 1 4
101 1/7/2016 0 0
101 1/8/2016 0 0
101 1/9/2016 1 2
101 1/10/2016 1 2
102 1/2/2016 1 3
102 1/3/2016 1 3
102 1/4/2016 1 3
102 1/5/2016 0 0
102 1/6/2016 0 0
102 1/7/2016 0 0
102 1/8/2016 1 4
102 1/9/2016 1 4
102 1/10/2016 1 4
102 1/11/2016 1 4
Thanks in advance for any assistance!
KC
This would be a lot easier to implement as part of the query you’re using to return the data, but if you have to do it in spotfire, I suggest this.
1- Create a hierarchy column containing [Corp_ID] and [Date] (Named ‘DateHr’)
2- Add a calculated column named ‘Concat Flags’ which concatenates all the previous flag values: Concatenate([Flagged]) OVER (Intersect(Parent([Hierarchy.DateHr]),allPrevious([Hierarchy.DateHr])))
3- Add a calculated column which will return the number of 0’s in the Concat Flags field (Named ‘# of 0s’): Len([Concat Flags]) - Len(Substitute([Concat Flags],"0",""))
4- Add a hierarchy column containing [Corp_ID] and [# of 0s] (Named ‘CorpHr’)
5- Add a calculated column to return your desired value: case when [Flagged]=1 then Sum([Flagged]) OVER (Intersect([Hierarchy.CorpHr])) else 0 end
Note: the above assumes you are working in Spotfire version 7.5. The syntax for using hierarchies in calculated columns differs slightly in earlier versions).
Related
How do I do this is excel. The example is provided below. If we don't sell any products on a specific day I would like to move those hours to the next date.
If you need to compute partial sums of Hours for all the consecutive rows between rows that satisfy the condition that the value Sold is greater than zero, you could do this with an auxiliary column
A B C D
---------------------------------
1 |Hours Sold Sums Solution
2 | 300 30 300 300
3 | 30 0 300 0
4 | 0 0 300 0
5 | 30 0 300 0
6 | 300 50 660 360
7 | 23 0 660 0
8 | 100 25 783 123
Here Sums is defined by a formula for C2
=IF(B2>0,SUM(A2:$A$2),C1)
You can automatically populate the cells below.
This formula puts in a cell a partial sum of Hours up to the current row if Sold is nonzero, otherwise copies the previous partial sum of hours. We need this to subtract this value on the next step.
When you have the column C filled, it is sufficient to put the following formula in D2 and populate the cells below
=IF(ROW(B2)>2,IF(B2>0,C2-C1,0),C2)
This formula handles correctly both D2 that does not have a preceding row with values and the remaining cells in column D.
In fact you could combine the two formulas together and avoid the need to have an auxiliary column. Put the following formula in C2 and spread it down to the rest of the cells in column C
=IF(ROW(B2)>2,IF(B2>0,SUM(A2:$A$2)-SUM(C1:$C$2),0),A2)
to get
A B C
---------------------------------
1 |Hours Sold Solution
2 | 300 30 300
3 | 30 0 0
4 | 0 0 0
5 | 30 0 0
6 | 300 50 360
7 | 23 0 0
8 | 100 25 123
I have typed out an equation that I have dragged it down in a column in my excel table. I think I’m fairly close… and would love some feedback around this.
I want cumulative sum of the first cell $J$3 to the cell row it’s currently on (J53 for example). And I want cumulative sum of the particular cells that meet these conditions (ie… COUNTIF($B$3:B53,B53)*COUNTIF(AC53,1).
I know the Sumif() statement below isn’t correct… but this was as close as I could get!
=IF((COUNTIF($B$3:B53,B53)*COUNTIF(AC53,1)),(SUMIF($J$3:J53,J53)),0)
As shown in the table below
Projectid(B)
successornot(AC)
production(J)
result I want
1
1
20
20
1
1
40
60
1
1
10
70
2
0
20
0
2
0
400
0
3
1
20
20
4
0
1
0
5
0
24
0
6
0
50
0
7
1
10
10
7
1
40
50
7
1
20
70
Give a try on
=IF(B2=0,0,SUMIFS($C$2:$C2,$A$2:$A2,A2,$B$2:$B2,">0"))
I need help for distinct count for duplicate value and output required as follows.
If Column A's value is 28 the result should be unique1(Column E) Else if Column A's value is 29 then the result should be Column F(Unique2)
Code Product Quantity Weight Unique1 Unique2
28 Apple 9 100 1 0
28 Orange 9 100 1 0
28 Apple 9 100 0 0
29 Apple 9 200 0 1
29 Apple 10 100 0 1
29 Apple 10 100 0 0
28 Orange 9 200 1 0
I tried Mr.tigeravatar code and it is working fine, but I don't know how to add an if ... else condition for checking and output in a different column.
For validation try this code: paste it in cell G2 or whatever preceding columns in row 2.
=IF(OR(AND(A2=28,E2=1,F2<>1),AND(A2=29,E2<>1,F2=1)),"Correct","Incorrect")
I have a dataframe which is grouped at product store day_id level Say it looks like the below and I need to create a column with rolling sum
prod store day_id visits
111 123 1 2
111 123 2 3
111 123 3 1
111 123 4 0
111 123 5 1
111 123 6 0
111 123 7 1
111 123 8 1
111 123 9 2
need to create a dataframe as below
prod store day_id visits rolling_4_sum cond
111 123 1 2 6 1
111 123 2 3 5 1
111 123 3 1 2 1
111 123 4 0 2 1
111 123 5 1 4 0
111 123 6 0 4 0
111 123 7 1 NA 0
111 123 8 1 NA 0
111 123 9 2 NA 0
i am looking for create a
cond column: that recursively checks a condition , say if rolling_4_sum is greater than 5 then make the next 4 rows as 1 else do nothing ,i.e. even if the condition is not met retain what was already filled before , do this check for each row until 7 th row.
How can i achieve this using python ? i am trying
d1['rolling_4_sum'] = d1.groupby(['prod', 'store']).visits.rolling(4).sum()
but getting an error.
The formation of rolling sums can be done with rolling method, using boxcar window:
df['rolling_4_sum'] = df.visits.rolling(4, win_type='boxcar', center=True).sum().shift(-2)
The shift by -2 is because you apparently want the sums to be placed at the left edge of the window.
Next, the condition about rolling sums being less than 4:
df['cond'] = 0
for k in range(1, 4):
df.loc[df.rolling_4_sum.shift(k) < 7, 'cond'] = 1
A new column is inserted and filled with 0; then for each k=1,2,3,4, look k steps back; if the sum then less than 7, then set the condition to 1.
I am looking for help to solve this excel problem.
Essentially I want to create a formula for cells in column F which does a multiple search on 3 criteria (on cells in columns A,B,C) and want to access the corresponding column D values where all these (multiple) matches occur, and sum this in column F. I'd also like a count of the amount of matches found to calculate the value in column F; placed alongside in column G.
e.g.
IF col_A_value (anywhere in whole A column) = current_col_A_value +/- 1
AND col_B_value (anywhere in whole B column) = current_col_B_value +/- 1
AND col_C_value (anywhere in whole C column) = current_col_C_value - 1
THEN (output in column F) the sum of all values from row D where this criteria is met
(also, as a seperate but related cell formula, output in column G) the total Count of times this occurs.
Note: the values in columns A,B,C are all integars and the +/- above means to search for any values which are either +1, 0, or -1 different in value. (i.e. this includes the value itself).
e.g. If the value in cell A1 = 10, B1 = 45, C1 = 881, then the first search criteria would look for all other rows with values of 9, 10 or 11 in column A. Then based on these rows, the second search criteria would refine the search to only those rows which also include either a 44, 45 or 46 in column B, and the third search criteria would refine the search again to only include those rows where the column C value is 880.
Next, the values in the column D cells from all of these 'filtered' rows would be summed and the result placed in the column F cell. (The count of these results rows would be put in column G. (seperate formula required))
Since these are all unique entries (think of columns A,B,C creating unique vector coordinates in space), there should be a maximum of 9 entries found and summed. A +/-1: 3 variations, B +/-1: 3 variations and C -1 only: 1 variation. In total: 3x3x1 = 9 unique rows maximum (and potentially none as a minimum, as in the below example).
(If no match is found a value of 0 is good.)
Example with A,B,C,D and E as given values, and column F values calculated (together with the count shown in col G):
A B C D E F G
1 1 1 90 8 0 0
1 2 1 80 6 0 0
1 3 1 70 1 0 0
1 4 1 60 6 0 0
2 1 1 50 1 0 0
2 2 1 40 8 0 0
2 3 1 30 6 0 0
2 4 1 20 8 0 0
3 1 1 10 8 0 0
3 2 1 11 6 0 0
3 3 1 12 1 0 0
3 4 1 13 1 0 0
1 1 2 99 8 260 4
1 2 2 89 6 360 6
1 3 2 79 1 300 6
1 4 2 69 6 180 4
2 1 2 59 1 281 6
2 2 2 49 8 393 9
etc
To illustrate how column F values are calculated here is the working:
260 = 90+80+50+40
360 = 90+80+70+50+40+30
300 = 80+70+60+40+30+20
180 = 70+60+30+20
281 = 90+80+50+40+10+11
393 = 90+80+70+50+40+30+10+11+12
Thanks a lot for any help with this!
These formulas should do what you desire:
F1: =SUMIFS(D:D,A:A,"<="&A1+1,A:A,">="&A1-1,B:B,"<="&B1+1,B:B,">="&B1-1,C:C,C1-1)
G1: =COUNTIFS(A:A,"<="&A1+1,A:A,">="&A1-1,B:B,"<="&B1+1,B:B,">="&B1-1,C:C,C1-1)
The formulas can simply be copied down as you need them...
(Still I don't know what col E is for)