When I am trying to show a few measures over a dimension (e.g. revenue per category) in a simple table, I am not able to add the dimension name to the table. It always looks like this:
| |revenue|clicks|
| 1234| 3.48| 5 |
| 5678| 100 | 1000 |
Is there a way, to show the result like this:
|category_id|revenue|clicks|
| 1234| 3.48| 5 |
| 5678| 100 | 1000 |
?
There is currently no option to display the name of the dimension in the table header. Nevertheless, for your example you could use the "Corner Text" option to display "Category ID".
Here is an example adding the "Years" dimension:
Related
I have table in RDS which consists two columns id and user activity at some time exactly values active/away.I get user activity every day so I need to add user activity column every day to that table.Any ideas how to do it?Now I have table with first two columns in RDS,but I am in stuck with how to add columns to that table
+-------------+------------+------------+
| id | 2020-08-13 | 2020-08-14 |
-----------------------------------------
| 12345 | active | away |
You could use an alter table ... add column, but this is not the right way to solve the problem.
In a relational database, you add additional rows for repeated data, not additional columns. So your table should look like this:
+-------------+-------------+------------+
| id | status_date | status |
------------------------------------------
| 12345 | 2020-08-13 | active |
| 12345 | 2020-08-14 | away |
Then you add a new row using an insert.
I have two tables (subject & category) that are both related to the same parent table (main). Because of the foreign key constraints, it looks like Power BI automatically created the links.
Simple mock-up of table links
I need to count the subjects by type for each possible distance range. I tried a simple calculation shown below for each distance category.
less than 2m =
CALCULATE(
COUNTA('Category'[Descr]),
'Subject'[Distance] IN { "less than 2m" }
)
However, the filter doesn't seem to apply properly.
I want...
+------+--------------+--------------+--+
| Descr| less than 2m | more than 2m | |
+------+--------------+--------------+--+
| Car | 2 | 1 | |
| Sign | 4 | 2 | |
+------+--------------+--------------+--+
but I'm getting...
+------+--------------+--------------+--+
| Descr| less than 2m | more than 2m | |
+------+--------------+--------------+--+
| Car | 3 | 3 | |
| Sign | 6 | 6 | |
+------+--------------+--------------+--+
It's just giving me the total count by type which is correct but isn't applying the filter by distance so I can break it down.
I'm sure this is probably really simple but I'm pretty new with DAX and I can't figure this one out.
I wish I could mark Kosuke's comment as an answer. The issue was indeed with having to enable cross-filtering. This can either be done clicking on the link on your model or using a function to temporarily enable the cross filter.
I have the following tables:
Table A:
___________________
| ID | NUMBER |
|__________|________|
| 10000378 | 1 |
| | |
Table B:
_________________________________________________
| ... | ID | Column 1 | Column 2 |
|____________|__________|____________|____________|
| ... | 10000378 | 7 | 2 |
| | | | |
Table A and Table B share the same ID value.
Not that it matters too much, the ID in Table A is it's key, and can be found in Table B.
Table A's NUMBER column tells me which Table B column to read.
For example:
IF
[Table A].[NUMBER] = 1
THEN
put the value of [Table B].[Column 1] into [Table B].[My Column]
... and so on
As a visual example (my desired result):
_______________________________________________________________
| ... | ID | Column 1 | Column 2 | My Column |
|____________|__________|____________|____________|_____________|
| ... | 10000378 | 7 | 2 | 7 |
| | | | | |
With My Column being the result I am after (which comes from Column 1 - as specified by Table A's NUMBER value for the ID of 10000378).
What I have tried so far
I have set up a 1-to-1 relationship between Table A and Table B (on the ID column`).
I then went into the Power Query Editor tried adding a Conditional Column:
But that doesn't allow me to reference Table A in any way.
So I decided to try the Append Queries as New option:
Selecting the Two tables radio button, setting Primary Table to Table B and Table to append to the primary table to Table B.
With the idea of creating the following structure from which I can get my desired result (but adding the NUMBER column, which I don't really want but can live with):
_____________________________________________________________________________
| ... | ID | Column 1 | Column 2 | NUMBER | My Column |
|____________|__________|____________|____________|_____________|_____________|
| ... | 10000378 | 7 | 2 | 1 | 7 |
| | | | | | |
Doing the append copied all of the contents of Table B and inserted the NUMBER column which is fine, but all the values in that NUMBER column are now null.
I don't understand why this is the case.
How can I achieve my desired result?
Appending queries is used when you have additional rows of data that you’d like to add to an existing query (i.e. union/union all in SQL). Joining tables in Power BI is called "merging":
You can find more details in Combine queries section of Tutorial: Shape and combine data in Power BI Desktop article.
Note that if you have a proper relationship defined between your tables in the model (also described in the article above).
To do this, first merge Table B with Table A and expand the columns you'd like to add to the table (Column 1 and Column 2).
Once you have that, then write your custom column, My Column:
if [NUMBER] = 1 then [Column 1]
else if [NUMBER] = 2 then [Column 2]
else <whatever you want to return if not 1 or 2>
I have two line plots that come from a different columns in measurement formulas but both share the time axis.
This is the first plot:
The second one:
In this case the second plot is just a scaled version of the first one, but the principle remains the same, I´m not able to just drag and drop the values from both measurements into the same "valores" box, it just iverwrites:
How can I plot this two measurements on the same box?
Something like the stacked areas plot but without the offset.
This is my data:
And the expresion fot the measurements I´m using:
Medida = CALCULATE(sum(test_data[Percentage_By_Class]);filter(test_data;test_data[Date]=max(test_data[Date]));
ALLEXCEPT(test_data;test_data[Score]))/ CALCULATE(sum(test_data[Percentage_By_Class]);
filter(all(test_data);test_data[Date]=max(test_data[Date])))
Medida2 = CALCULATE(sum(test_data[Percentage_By_Class]);filter(test_data;test_data[Date]=max(test_data[Date]));
ALLEXCEPT(test_data;test_data[Score]))/ CALCULATE(1.3*sum(test_data[Percentage_By_Class]);
filter(all(test_data);test_data[Date]=max(test_data[Date])))
And a google drive link to download the used data in CSV format:
https://drive.google.com/file/d/1dEdUwwofv1OQ9rOGQMuyfYKO9_YJDTcl/view?usp=sharing
I don't think there's a nice built-in way to do this, but here's a possible workaround:
Create a new table for the legend which will be the Cartesian product of scores and measures.
Legend =
ADDCOLUMNS(
CROSSJOIN(VALUES(test_data[Score]), {1,2}),
"Legend", [Score] & [Value]
)
This table should like this:
| Score | Value | Legend |
|-------|-------|--------|
| A | 1 | A1 |
| C | 1 | C1 |
| B | 1 | B1 |
| A | 2 | A2 |
| C | 2 | C2 |
| B | 2 | B2 |
Now create a combined measure that switches between [Medida] and [Medida2]:
Combo =
IF(
SELECTEDVALUE(Legend[Value]) = 1,
CALCULATE([Medida], test_data[Score] in VALUES(Legend[Score])),
CALCULATE([Medida2], test_data[Score] in VALUES(Legend[Score]))
)
Then if you put Legend in the legend box and Combo in the values box, you should get a chart like this:
You can change the colors too if you want to visually group the lines.
I am parsing the USDA's food database and storing it in SQLite for query purposes. Each food has associated with it the quantities of the same 162 nutrients. It appears that the list of nutrients (name and units) has not changed in quite a while, and since this is a hobby project I don't expect to follow any sudden changes anyway. But each food does have a unique quantity associated with each nutrient.
So, how does one go about storing this kind of information sanely. My priorities are multi-programming language friendly (Python and C++ having preference), sanity for me as coder, and ease of retrieving nutrient sets to sum or plot over time.
The two things that I had thought of so far were 162 columns (which I'm not particularly fond of, but it does make the queries simpler), or a food table that has a link to a nutrient_list table that then links to a static table with the nutrient name and units. The second seems more flexible i ncase my expectations are wrong, but I wouldn't even know where to begin on writing the queries for sums and time series.
Thanks
You should read up a bit on database normalization. Most of the normalization stuff is quite intuitive, but really going through the definition of the steps and seeing an example helps understanding the concepts and will help you greatly if you want to design a database in the future.
As for this problem, I would suggest you use 3 tables: one for the foods (let's call it foods), one for the nutrients (nutrients), and one for the specific nutrients of each food (foods_nutrients).
The foods table should have a unique index for referencing and the food's name. If the food has other data associated to it (maybe a link to a picture or a description), this data should also go here. Each separate food will get a row in this table.
The nutrients table should also have a unique index for referencing and the nutrient's name. Each of your 162 nutrients will get a row in this table.
Then you have the crossover table containing the nutrient values for each food. This table has three columns: food_id, nutrient_id and value. Each food gets 162 rows inside this table, oe for each nutrient.
This way, you can add or delete nutrients and foods as you like and query everything independent of programming language (well, using SQL, but you'll have to use that anyway :) ).
Let's try an example. We have 2 foods in the foods table and 3 nutrients in the nutrients table:
+------------------+
| foods |
+---------+--------+
| food_id | name |
+---------+--------+
| 1 | Banana |
| 2 | Apple |
+---------+--------+
+-------------------------+
| nutrients |
+-------------+-----------+
| nutrient_id | name |
+-------------+-----------+
| 1 | Potassium |
| 2 | Vitamin C |
| 3 | Sugar |
+-------------+-----------+
+-------------------------------+
| foods_nutrients |
+---------+-------------+-------+
| food_id | nutrient_id | value |
+---------+-------------+-------+
| 1 | 1 | 1000 |
| 1 | 2 | 12 |
| 1 | 3 | 1 |
| 2 | 1 | 3 |
| 2 | 2 | 7 |
| 2 | 3 | 98 |
+---------+-------------+-------+
Now, to get the potassium content of a banana, your'd query:
SELECT food_nutrients.value
FROM food_nutrients, foods, nutrients
WHERE foods_nutrients.food_id = foods.food_id
AND foods_nutrients.nutrient_id = nutrients.nutrient_id
AND foods.name = 'Banana'
AND nutrients.name = 'Potassium';
Use the second (more normalized) approach.
You could even get away with fewer tables than you mentioned:
tblNutrients
-- NutrientID
-- NutrientName
-- NutrientUOM (unit of measure)
-- Otherstuff
tblFood
-- FoodId
-- FoodName
-- Otherstuff
tblFoodNutrients
-- FoodID (FK)
-- NutrientID (FK)
-- UOMCount
It will be a nightmare to maintain a 160+ field database.
If there is a time element involved too (can measurements change?) then you could add a date field to the nutrient and/or the foodnutrient table depending on what could change.