PowerBI: Use non-shown values for Drillthrough - powerbi

I am trying to build a Power BI report for data from a SQL database where I have to show detail pages using Drillthrough. The only viable way to connect the datasets is using the database row ids.
From a user's perspective the row ids would not add any value but a lot of noise.
Is there a way to drillthrough using the row ids without showing them in a visual?

Yes, this is possible in the current release of Power Bi Desktop using a workaround solution that involves hiding the row id column in the parent (or summary) page.
Take the following tables as example:
ALBUM
+---------+------------------------+
| AlbumId | AlbumName |
+---------+------------------------+
| 1 | Hoist |
+---------+------------------------+
| 2 | The Story Of the Ghost |
+---------+------------------------+
TRACK
+---------+---------+--------------------------+
| TrackId | AlbumId | TrackName |
+---------+---------+--------------------------+
| 1 | 1 | Julius |
+---------+---------+--------------------------+
| 2 | 1 | Down With Disease |
+---------+---------+--------------------------+
| 3 | 1 | If I Could |
+---------+---------+--------------------------+
| 4 | 1 | Riker's Mailbox |
+---------+---------+--------------------------+
| 5 | 1 | Axilla, Part II |
+---------+---------+--------------------------+
| 6 | 1 | Lifeboy |
+---------+---------+--------------------------+
| 7 | 1 | Sample In a Jar |
+---------+---------+--------------------------+
| 8 | 1 | Wolfmans Brother |
+---------+---------+--------------------------+
| 9 | 1 | Scent of a Mule |
+---------+---------+--------------------------+
| 10 | 1 | Dog Faced Boy |
+---------+---------+--------------------------+
| 11 | 1 | Demand |
+---------+---------+--------------------------+
| 12 | 2 | Ghost |
+---------+---------+--------------------------+
| 13 | 2 | Birds of a Feather |
+---------+---------+--------------------------+
| 14 | 2 | Meat |
+---------+---------+--------------------------+
| 15 | 2 | Guyute |
+---------+---------+--------------------------+
| 16 | 2 | Fikus |
+---------+---------+--------------------------+
| 17 | 2 | Shafty |
+---------+---------+--------------------------+
| 18 | 2 | Limb by Limb |
+---------+---------+--------------------------+
| 19 | 2 | Frankie Says |
+---------+---------+--------------------------+
| 20 | 2 | Brian and Robert |
+---------+---------+--------------------------+
| 21 | 2 | Water in the Sky |
+---------+---------+--------------------------+
| 22 | 2 | Roggae |
+---------+---------+--------------------------+
| 23 | 2 | Wading in the Velvet Sea |
+---------+---------+--------------------------+
| 24 | 2 | The Moma Dance |
+---------+---------+--------------------------+
| 25 | 2 | End of Session |
+---------+---------+--------------------------+
Add them as data sources. The 1:many relationship between AlbumId should be created. Create a parent page with a table containing AlbumId and AlbumName. Then create the details page with a table containing only the TrackName column. In the Drillthrough filter field of the details page, drag the Album Table -> AlbumId to this field.
Now go back to the parent page and notice that when you right click on an album, you get the drillthrough menu to the details page. This works, but now you have a messy AlbumId column on your parent page.
The workaround is to hide the AlbumId on the parent report. First go to the Format(Paint roller) menu of the table on the parent report and in the column header -> word wrap turn this off. Then drag the column separator of the table to hide the AlbumId. See before and after images below.
BEFORE HIDE
AFTER HIDE
I have the powerbi file posted here if you want to see it in action.

Related

How do I repeat row labels in a matrix?

I have data showing me the dates grouped like this:
For security reasons, I had to remove the Customer Description detail, due to confidentiality.
How do I repeat the date column the same way you repeat the Row Labels in an Excel Pivot?
I've looked, but couldn't find a solution to this - this option should be available.
EDIT
When you have the following source data in Excel:
Date | Customer | Item Description | Qty Out | Unit Price | Sales
--------------------------------------------------------------------------------------------------------------------------------------------
14/08/2020 | Customer 1 | Item 11 | 4.00 | 65.00 | 260.00
14/08/2020 | Customer 2 | Item 12 | 56.00 | 12.00 | 672.00
14/08/2020 | Customer 3 | Item 13 | 64.00 | 35.00 | 2,240.00
14/08/2020 | Customer 4 | Item 14 | 29.00 | 65.00 | 1,885.00
15/08/2020 | Customer 2 | Item 15 | 746.00 | 12.00 | 8,952.00
15/08/2020 | Customer 3 | Item 16 | 14.00 | 75.00 | 1,050.00
15/08/2020 | Customer 4 | Item 17 | 45.00 | 741.00 | 33,345.00
15/08/2020 | Customer 5 | Item 18 | 456.00 | 125.00 | 57,000.00
15/08/2020 | Customer 6 | Item 19 | 925.00 | 17.00 | 15,725.00
16/08/2020 | Customer 4 | Item 20 | 6.00 | 532.00 | 3,192.00
16/08/2020 | Customer 5 | Item 21 | 56.00 | 94.00 | 5,264.00
16/08/2020 | Customer 6 | Item 22 | 546.00 | 37.00 | 20,202.00
You then pivot this data using Microsoft Excel, where you get the following:
You then choose the option to Repeat Item Labels as can be seen below:
After selecting this, you get my expected results I require in Power BI:
Is there not a function available like this in Power BI?
Just adding this for your reference as a work around. Check this below image with a custom column created in the Power Query Editor-
date_customer = Date.ToText([Date]) &" : "& [Customer]
Then added both Date and date_customer in the Matrix row level. The output is as below- (using your sample data)
ANOTHER OPTION Another option is to add Date and Customer in the Matrix row and the output is will be as below- (using your sample data)
This is also a meaningful output as date are showing as a group header. But in case of requirement of having redundant date to show, you can consider the first option.

sqlite window function to get difference and product

I am using a window function to get the difference in the values of a column (downloads) between two dates. I'd also like to get the product of that difference multiplied by the size of the file to get the bytes downloaded for the period.
With the help of this community, I am able to get the number of downloads but cannot find the correct syntax to get the product of downloads * size.
Table 'files'
+---------------+------------------------+------+-----------+------------+
| site | full_path | size | downloads | date_stamp |
+---------------+------------------------+------+-----------+------------+
| Lawrenceville | lr1/dir1/subdir1/file1 | 1000 | 7 | 2019-08-08 |
| Lawrenceville | lr1/dir1/subdir1/file1 | 1010 | 9 | 2019-08-15 |
| Lawrenceville | lr1/dir1/subdir1/file2 | 1213 | 5 | 2019-08-08 |
| Lawrenceville | lr1/dir1/subdir1/file2 | 2000 | 5 | 2019-08-15 |
| Lawrenceville | lr1/dir2/subdir1/file1 | 2213 | 5 | 2019-08-15 |
| Rennes | rr1/dir1/subdir1/file3 | 200 | 3 | 2019-08-08 |
| Rennes | rr1/dir1/subdir1/file3 | 201 | 4 | 2019-08-15 |
+---------------+------------------------+------+-----------+------------+
SELECT site, sum(diff) FROM (SELECT site, downloads - lag(downloads, 1) OVER (PARTITION BY site, full_path ORDER BY date_stamp) AS diff FROM files WHERE date_stamp IN ('2019-08-15', '2019-08-08')) group by site
produces this:
+---------------+-----------+
| site | downloads |
+---------------+-----------+
| Lawrenceville | 2 |
| Rennes | 1 |
+---------------+-----------+
I have tried:
SELECT site, sum(diff), sum(sum(diff)*bytes) FROM (SELECT site, downloads - lag(downloads, 1), size OVER (PARTITION BY site, full_path ORDER BY date_stamp) AS diff, bytes FROM files WHERE date_stamp IN ('2019-08-15', '2019-08-08')) group by site
sqlite3.OperationalError: near "(": syntax error
Ideally I want this output:
+---------------+-----------+----------+
| site | downloads | bytes |
+---------------+-----------+----------+
| Lawrenceville | 2 | 2020 |
| Rennes | 1 | 201 |
+---------------+-----------+----------+
Lawrenceville had 2 downloads of file lr1/dir1/subdir1/file1 which is 1010 bytes (on 2019-08-15). File lr1/dir1/subdir1/file2 had no downloads for that period. It would be nice to include files lr1/dir1/subdir1/file2 and lr1/dir2/subdir1/file1 but they get excluded by the window function. I can get them with a separate query.
Rennes has 1 download of file rr1/dir1/subdir1/file3
If your current query works then you only need max() window function in the subquery:
SELECT site, sum(diff) downloads, sum(diff) * size bytes
FROM (
SELECT
site,
downloads - lag(downloads, 1) OVER (PARTITION BY site, full_path ORDER BY date_stamp) AS diff,
max(size) OVER (PARTITION BY site, full_path) AS size
FROM files
WHERE date_stamp IN ('2019-08-15', '2019-08-08')
)
group by site
See the demo.
Results:
| site | downloads | bytes |
| ------------- | --------- | ----- |
| Lawrenceville | 2 | 2020 |
| Rennes | 1 | 201 |

unique column value per row

I find it best to use an example, so here we go:
Say I have a table with chores and a table with a weekly schedule like this:
CHORES:
|----+---------------+----------+-------|
| id | name | type | hours |
|----+---------------+----------+-------|
| 1 | clean kitchen | cleaning | 4 |
|----+---------------+----------+-------|
| 2 | clean toilet | cleaning | 3 |
etc
SCHEDULE:
|------+---------------+---------------+-----|
| week | monday | tuesday | etc |
|------+---------------+---------------+-----|
| 1 | clean kitchen | clean toilet | etc |
|------+---------------+---------------+-----|
| 2 | clean toilet | clean kitchen | etc |
etc
I want to make sure that for one week, you can't have duplicate cells, so this wouldn't be allowed:
SCHEDULE:
|------+---------------+--------------+-----|
| week | monday | tuesday | etc |
|------+---------------+--------------+-----|
| 1 | clean toilet | clean toilet | etc |
etc
What would I have to do in my models.py to get this behaviour?
Try django unique-together in model meta option.
https://docs.djangoproject.com/en/1.11/ref/models/options/#unique-together
I'd better user ManyToMany through another table like that:
SCHEDULE:
------+------------------------+
| week | chores |
|------+------------------------+
| 1 | many to many to chores |
|------+------------------------+
| 2 | many to many to chores |
And trough table like that
THROUGH TABLE:
|---------+---------------+---------------+
| week_id | day of week | chores_id |
|---------+---------------+---------------+
| 1 | Monday | clean toilet |
|---------+---------------+---------------+
| 1 | Tuesday | clean kitchen |
And in that table make unique together for week_id and chores_id

How to run raw query with a model with dynamic fields in Django 1.9?

I have a complex result that requires writing raw sql queries.
See https://stackoverflow.com/a/38548462/80353
The expected result is a table showing several columns.
The first column header is simply Product and the other column headers are store names.
The values are simply the product names and the aggregated sales values of the product in these stores.
Which stores will be shown is entirely dynamic. Maximum should be 9 stores.
The same in text format:
Store table
------------------------------
| id | code | address |
|-----|------|---------------|
| 1 | S1 | Kings Row |
| 2 | S2 | Queens Street |
| 3 | S3 | Jacks Place |
| 4 | S4 | Diamonds Alley|
| 5 | S5 | Hearts Road |
------------------------------
Product table
------------------------------
| id | code | name |
|-----|------|---------------|
| 1 | P1 | Saucer 12 |
| 2 | P2 | Plate 15 |
| 3 | P3 | Saucer 13 |
| 4 | P4 | Saucer 14 |
| 5 | P5 | Plate 16 |
| and many more .... |
|1000 |P1000 | Bowl 25 |
|----------------------------|
Sales table
----------------------------------------
| id | product_id | store_id | amount |
|-----|------------|----------|--------|
| 1 | 1 | 1 |7.05 |
| 2 | 1 | 2 |9.00 |
| 3 | 2 | 3 |1.00 |
| 4 | 2 | 3 |1.00 |
| 5 | 2 | 5 |1.00 |
| and many more .... |
| 1000| 20 | 4 |1.00 |
|--------------------------------------|
The relationships are:
Sales belongs to Store
Sales belongs to Product
Store has many Sales
Product has many Sales
What I want to achieve
I want to display by pagination in the following manner:
Given the stores S1-S3:
-------------------------
| product | S1 | S2 | S3 |
|---------|----|----|----|
|Saucer 12|7.05|9 | 0 |
|Plate 15 |0 |0 | 2 |
| and many more .... |
|------------------------|
For more details of the schema, check the question in How to get back aggregate values across 2 dimensions using Python Cubes?
My question
The schema is not super important to my question which is:
Since I am going to write a complex raw query, is there a way to map the query result to a model where the fields are dynamic?
I found documentation about how to execute raw queries in Django and how to execute raw queries to existing models with fixed fields and matching table.
My question is is it possible to do that for a model that has no matching table and dynamic fields?
If so, how?
Or if I choose to use materialised view in postgresql, how do I match it with a model class?

PostgreSQL - splitting rows using regex

I have got a table that has got colums ID, name and description. Table looks like:
ID | Name | Model
1 | Ford | Focus 3
2.1-3 | Opel | 1. Astra 2
| | 2. Vectra 2
| | 3. Vectra 3
3.1-2 | Toyota| Avensis 2; Micra
4.1-2 | Opel | (various versions) 1. Astra
| | (various versions) 2. Vectra
5.1-3 | Mazda | MX5; GTR; MX4
And I would like to split it into new rows using "regexp_split_to_table"
To get result like this:
ID | Name | Description
1 | Ford | Focus 3
2.1 | Opel | Astra 2
2.2 | Opel | Vectra 2
2.3 | Opel | Vectra 3
3.1 | Toyota| Avensis
3.2 | Toyota| Micra
4.1 | Opel | Astra
4.2 | Opel | Vectra
5.1 | Mazda | MX5
5.2 | Mazda | GTR
5.3 | Mazda | MX4
How to do it using postresql and update main table after that?
Big thanks for your help!
Generally it is impossible for several reasons:
Your data is not ordered, for your example it is possible to have something like
ID | Name | Description
| | (year) 2. 2004
1 | Ford | Some text
5.1-3 | Mazda | Petrol; 1.9; 3-doors
| | 2. Diesel
2.1-3 | Opel | 1. Astra
| | 3. 2005
3 | Toyota| 2001; Petrol; 1.8 TDI
4.1-2 | Opel | (model) 1. Vectra
Just try something like
drop table if exists my_ugly_table;
create table my_ugly_table as select generate_series(1,3) as x, generate_series(1,3) as y;
select * from my_ugly_table;
update my_ugly_table set y = 4 where x = 2;
select * from my_ugly_table;
and you will have
first result:
x | y
---+---
1 | 1
2 | 2
3 | 3
(3 rows)
second result:
x | y
---+---
1 | 1
3 | 3
2 | 4
(3 rows)
As you can see row order was changed.
Next, your goal is wrong at the point that you want to keep in the ID some valuable data like 1.2, 1.3 and so on. ID must be just a unique identifier of the row and nothing else. Ideally you have no any knowledge about values of IDs - them just exists.
However you can try do do something with your original data using plpgsql or something like:
First of all create table where we will performing something bad with our data:
create table models_t as select * from models m where 1=2;
It will create empty table models_t with structure same to table models.
Finally for them lets create truly PK:
alter table models_t add mt_id serial not null primary key;
Next lets fill it by data:
do language plpgsql $$
declare
p_rec models;
c_rec models;
begin
p_rec := null;
for c_rec in (select * from models) loop
p_rec.id := coalesce(c_rec.id, p_rec.id);
p_rec.name := coalesce(c_rec.name, p_rec.name);
p_rec.description := c_rec.description;
insert into models_t values (p_rec.id, p_rec.name, p_rec.description);
raise notice '% %', c_rec.id, c_rec.name;
end loop;
end; $$;
Only one result of it is that we have table without gaps like:
postgres=# select * from models_t;
id | name | description | mt_id
-------+--------+----------------------+-------
1 | Ford | Some text | 1
2.1-3 | Opel | 1. Astra | 2
2.1-3 | Opel | 2. Diesel | 3
2.1-3 | Opel | 3. 2005 | 4
3 | Toyota | 2001; Ptrol; 1.8 TDI | 5
4.1-2 | Opel | (model) 1. Vectra | 6
4.1-2 | Opel | (year) 2. 2004 | 7
5.1-3 | Mazda | Petrol; 1.9; 3-doors | 8
(8 rows)
Actually it is enough. However, lets parse our last data:
select
*,
substring(id from '(\d*)\.?.*') as main_id, -- First number before dot
row_number() over (partition by substring(id from '(\d*)\.?.*')) as secondary_id -- Order inside previous value
from models_t;
Result:
id | name | description | mt_id | main_id | secondary_id
-------+--------+----------------------+-------+---------+--------------
1 | Ford | Some text | 1 | 1 | 1
2.1-3 | Opel | 1. Astra | 2 | 2 | 1
2.1-3 | Opel | 2. Diesel | 3 | 2 | 2
2.1-3 | Opel | 3. 2005 | 4 | 2 | 3
3 | Toyota | 2001; Ptrol; 1.8 TDI | 5 | 3 | 1
4.1-2 | Opel | (model) 1. Vectra | 6 | 4 | 1
4.1-2 | Opel | (year) 2. 2004 | 7 | 4 | 2
5.1-3 | Mazda | Petrol; 1.9; 3-doors | 8 | 5 | 1
(8 rows)
At that point we can use columns main_id and secondary_id to build wanted IDs like 1.1 or 2.3.
Everything other is up to you.
Good luck and have fun.