So here's how the database is designed:
People
Entities
Hours
There are multiple people and multiple entities. I need to calculate each person's per entity total and the percentage of that total towards their total hours. So here's an example:
The database:
Name Entity 5
Person1 Entity 1 5
Person1 Entity 2 10
Person1 Entity 1 10
Person1 Entity 2 2
Person2 Entity 1 12
Person2 Entity 1 8
Person2 Entity 1 5
Person2 Entity 2 15
Expected Result:
Name Entity Total Hours Percent Percent Expected (against 40)
Person1 Entity 1 15 56% 37.5%
Person1 Entity 2 12 44% 30%
Person2 Entity 1 25 62.5% 62.5%
Person2 Entity 2 15 37.5% 37.5%
I can display the total hours for each entity per person, but I'm not sure how to grab the total of their hours while also calculating each entity's total hours against the total hours of each person while separately calculating the total of each entities hours (per person) against a static number.
It's not as complex as it sounds, and if this were Excel it would be a breeze, but doing it in FileMaker has proven a bit more challenging.
Place these fields in a sub-summary by Entity part (next to the Name and Entity fields):
This is assuming the "expected" value of 40 is supposed to be hard-coded (although you could take it from a global field or another calculation).
Related
I`m storing a hierarchical product adjacency list and a separate table for all the sales on those products.
Currently, I`m trying to present to the user a "Sales Report" with the total amount/sum sold per each product, and at the parent level.
In the sales table, I do not have info on the sales per group, thus, I have info available only at the level of the child. From what I have read I need to use recursive CTE, and I tried creating some queries, without any success.
Example of my dataset:
F - folders
P - products
Products table:
id
name
parentid
1
F1
NULL
2
F2
1
3
P1
2
4
P2
2
Sales table:
id
quant
sum
3
3
90
4
2
100
What I need to obtain in the report:
id
name
parentid
quant
sum
1
F1
NULL
5
190
2
F2
1
5
190
3
P1
2
3
90
4
P2
2
2
100
Logically, I understand that I need to fetch each row, and recursively go through all its children in order to SUM the quant and the sum, however I have no clue how to write it.
I`d be thankful for any guidance on where I could read more about recursive CTE, or anything that can help my situation.
Cheers!
We host data for an auditing service. Every few months, a new audit comes out with similar questions to previous audits of the same category. Since questions can change verbiage and number, we store each question in each audit separately (we do link them through a "related_questions" table).
audits
id
name
passing_score
1
audit_1
100
2
audit_2
150
questions
id
audit_id
text
1
1
q1
2
1
q2
3
2
q1
4
2
q2
We then have a surveys and responses table. Surveys are the overall response to an audit, while responses store the individual responses to each question.
surveys
id
audit_id
overall_score
pass
1
1
120
true
2
1
95
false
3
2
200
true
4
2
100
false
responses
id
survey_id
question_id
score
1
1
1
60
2
1
2
60
3
2
1
60
4
2
2
35
5
3
3
100
6
3
4
100
7
4
3
50
8
4
4
50
The analyze threshold is base threshold + scale factor * number of tuples. The problem with this is that once an audit has finished (after a few months), we'll never receive new surveys or responses for that category of data. The new data that comes in is conceptually all that needs to be analyzed. All data is queried, but the new data has the most traffic.
If 10% is the ideal scale factor for today and analyze autoruns once every week, a couple years from now analyze may autorun once every 4 months due to the number of tuples. This is problematic when the past 3 months of data is for questions that the analyzer has never seen and so there are no helpful stats for the query planner on this data.
We could set the scale factor extremely low for this table, but that seems like a cheap solution that could cause issues in the future.
If you have a constant data modifications rate, setting autovacuum_analyze_scale_factor to 0 for that table and only using autovacuum_analyze_threshold is a good idea.
This seems like a simple question but I'm having trouble building my graph. I'm trying to get the number of customers who made 1 order, 2 orders, 3 orders etc..
Sample Data Source:
Customer ID| Order ID| Date Ordered
A 10 06/01/2019
A 11 06/02/2019
A 12 06/02/2019
B 15 06/05/2019
B 16 06/05/2019
B 17 06/05/2019
C 20 06/06/2019
C 21 06/06/2019
I can easily get the graph to show that Customer A made 3 Orders , Customer B made 3 Orders and Customer C made 2 orders.. etc.
What I'm trying to show is how many customer places a certain number of orders . So in our sample data. 1 Order = 0 , 2 Orders = 1, 3 Orders = 2. So in the X axis im trying to show (1 Order, 2 Orders , 3 Orders, 4 Orders.. etc )
I tried doing calculations such as IF COUNT([CustomerID]) > 2 then '1 order' but I can't seem to get it right. Any advice will be helpful. Thanks in advance
Maybe you can try using LOD expressions and create a new calculated field like this:
{INCLUDE [Customer ID]: COUNTD([Order ID])}
And then use that field to show that info.
I need to create a dummy for the top purchase months within each customer ID. That is, if a month belong to one of the four months within the year where the customer purchased the most then it is noted with the number 1, otherwise 0.
Example of data, cust id, order date, volume and new variable dummy:
This code creates some sample data:
data list free/ID volume (2f4).
begin data
1 100 1 500 2 1 2 2 2 3 2 90 1 600 1 90 1 870 2 9 2 8 2 10
end data.
Using the sample data in the question, this code will create a new variable containing the dummy according to your definition:
RANK VARIABLES=volume (A) BY ID /RANK.
compute high4=(Rvolume<=4).
I am trying to consolidate the records on my report to show only unique lanes (Shipper State and Destination State).
My data is currently grouped by customer group and then customers that fall within each group.
Ideally I would like my data to fit in this format.
LANE ACCEPTED Total Percentage
Customer Group: Fruits
Customer: Apple
GA-TN 1 2 50%
GA-FL 2 3 66%
Customer: Bannana
GA-TN 2 4 50%
Total 5 9 55%
Currently my data looks like the image attached.
Thank you in advance.
1) Consolidated the Lanes by creating it in Formula Field, followed by creating adding it to the Group