I calculate my metrics with SQL and publish the resulting table to Tableau Server. Afterward, use this data source to create charts and dashboards.
For one analysis, I already calculated the measures per day with SQL. When I use the resulting table in Tableau, it aggregates these measures to SUM by default. However, I don't want to have SUM or AVG of the average or SUM of the Percentiles.
What I want is the result when I don't select date dimension and not GROUP BY date in SQL as attached below.
Here is the query:
SELECT
-- date,
COUNT(DISTINCT id) AS count_of_id,
AVG(timediff_in_sec) AS avg_timediff,
PERCENTILE_CONT(0.25) WITHIN GROUP(ORDER BY timediff_in_sec) AS percentile_25,
PERCENTILE_CONT(0.50) WITHIN GROUP(ORDER BY timediff_in_sec) AS percentile_50
FROM
(
--subquery
) AS t1
-- GROUP BY date
Here are the first 10 rows of the resulting table:
+------------+--------------+-------------+---------------+---------------+
| date | avg_timediff | count_of_id | percentile_25 | percentile_50 |
+------------+--------------+-------------+---------------+---------------+
| 10/06/2020 | 61,65186364 | 22 | 8,5765 | 13,3015 |
| 11/06/2020 | 127,2913333 | 3 | 15,6045 | 17,494 |
| 12/06/2020 | 306,0348214 | 28 | 12,2565 | 17,629 |
| 13/06/2020 | 13,2664 | 5 | 11,944 | 13,862 |
| 14/06/2020 | 16,728 | 7 | 14,021 | 17,187 |
| 15/06/2020 | 398,6424595 | 37 | 11,893 | 19,271 |
| 16/06/2020 | 293,6925152 | 33 | 12,527 | 17,134 |
| 17/06/2020 | 155,6554286 | 21 | 13,452 | 16,715 |
| 18/06/2020 | 383,8101429 | 7 | 266,048 | 493,722 |
+------------+--------------+-------------+---------------+---------------+
How can I achieve the desired output above?
Drag them all into the dimensions list, then they will be static dimensions. For your use you could also just drag the Date field to Rows. Aggregating 1 value, which you have for each date, returns the same value whatever the aggregation type.
Related
I have an "Orders" table:
+---------+-------------+
| OrderID | InvoiceDate |
+---------+-------------+
| 1 | 15/02/2022 |
| 123 | 20/01/2022 |
+---------+-------------+
and a "Rows" table:
+---------+-------+--------+
| OrderID | RowID | Value |
+---------+-------+--------+
| 1 | 1 | 100,00 |
| 1 | 2 | 200,00 |
| 1 | 3 | 50,00 |
| 123 | 1 | 10,00 |
| 123 | 2 | 20,00 |
+---------+-------+--------+
As shown in the example, it may happen that an order with a higher OrderID value has a lower InvoiceDate value.
In my report I would like to show each order, along with the sum of each row's value, ordered by date:
+-------------+---------+--------+
| InvoiceDate | OrderID | Value |
+-------------+---------+--------+
| 20/01/2022 | 123 | 30,00 |
| 15/02/2022 | 1 | 350,00 |
+-------------+---------+--------+
My problem is that in order to create an OrderValue formula field with Sum({Rows.Value}, {Orders.OrderID}), I first need to group by Rows.OrderID
But this way rows are sorted by OrderID, and I don't know how to sort them by date.
Add a group total of Maximum (or minimum, or Average) Order Date by Order ID.
Go to the menu option of Report, Group Sort Expert...
and sort the groups by that total.
I am struggling to do a loop on a Postgres, but functions on postgres are not my piece of cake.
I have the following table on postgres:
| portfolio_1 | total_risk |
|----------------|------------|
| Top 10 Bets | |
| AAPL34 | 2,06699 |
| DISB34 | 1,712684 |
| PETR4 | 0,753324 |
| PETR3 | 0,087767 |
| VALE3 | 0,086346 |
| LREN3 | 0,055108 |
| AMZO34 | 0,0 |
| Bottom 10 Bets | |
| AAPL34 | 0,0 |
What I'm trying to do is get the values after the "Top 10 Bets" and before the "Botton 10 Bets".
My goal is the following result:
| portfolio_1 | total_risk |
|-------------|------------|
| AAPL34 | 2,06699 |
| DISB34 | 1,712684 |
| PETR4 | 0,753324 |
| PETR3 | 0,087767 |
| VALE3 | 0,086346 |
| LREN3 | 0,055108 |
| AMZO34 | 0,0 |
So, my goal is to take off the "Top 10 Bets", the "Botton 10 Bets" and the AAPL34 after the "Botton 10 Bets", which was repeated.
The quantity of rows is variable (I'm importing it from an Excel file), so I need a loop to do this, right?
SQL tables and result sets represent unordered sets. There is no "before" or "after" unless rows explicitly provide that information.
Let me assume that you have such a column, which I will call id for convenience.
Then you can do this in several ways. Here is one:
select t.*
from t
where t.id > (select min(t2.id) from t t2 where t2.portfolio_1 = 'Top 10 Bets') and
t.id < (select max(t2.id) from t t2 where t2.portfolio_1 = 'Bottom 10 Bets');
I have the following table that I have loaded in Tableau (It has only one column CreatedOnDate)
+-----------------+
| CreatedOnDate |
+-----------------+
| 1/1/2016 |
| 1/2/2016 |
| 1/3/2016 |
| 1/4/2016 |
| 1/5/2016 |
| 1/6/2016 |
| 1/7/2016 |
| 1/8/2016 |
| 1/9/2016 |
| 1/10/2016 |
| 1/11/2016 |
| 1/12/2016 |
| 1/13/2016 |
| 1/14/2016 |
+-----------------+
I want to be able to find the maximum date in the table, compare it with every date in the table and get the difference in days. For the above table, the maximum date in table is 1/14/2016. Every date is compared to 1/14/2016 to find the difference.
Expected Output
+-----------------+------------+
| CreatedOnDate | Difference |
+-----------------+------------+
| 1/1/2016 | 13 |
| 1/2/2016 | 12 |
| 1/3/2016 | 11 |
| 1/4/2016 | 10 |
| 1/5/2016 | 9 |
| 1/6/2016 | 8 |
| 1/7/2016 | 7 |
| 1/8/2016 | 6 |
| 1/9/2016 | 5 |
| 1/10/2016 | 4 |
| 1/11/2016 | 3 |
| 1/12/2016 | 2 |
| 1/13/2016 | 1 |
| 1/14/2016 | 0 |
+-----------------+------------+
My goal is to create this Difference calculated field. I am struggling to find a way to do this using DATEDIFF.
And help would be appreciated!!
woodhead92, this approach would work, but means you have to use table calculations. Much more flexible approach (available since v8) is Level of Details expressions:
First, define a MAX date for the whole dataset with this calculated field called MaxDate LOD:
{FIXED : MAX(CreatedOnDate) }
This will always calculate the maximum date on table (will overwrite filters as well, if you need to reflect them, make sure you add them to context.
Then you can use pretty much the same calculated field, but no need for ATTR or Table Calculations:
DATEDIFF('day', [CreatedOnDate], [MaxDate LOD])
Hope this helps!
For example, if I have a database table of transactions done over the counter. And I would like to search whether there was any time that was defined as extremely busy (Processed more than 10 transaction in the span of 10 minutes). How would I go about querying it? Could I aggregate based on time range and count the amount of transaction id within those ranges?
Adding example to clarify my input and desired output:
+----+--------------------+
| Id | register_timestamp |
+----+--------------------+
| 25 | 08:10:50 |
| 26 | 09:07:36 |
| 27 | 09:08:06 |
| 28 | 09:08:35 |
| 29 | 09:12:08 |
| 30 | 09:12:18 |
| 31 | 09:12:44 |
| 32 | 09:15:29 |
| 33 | 09:15:47 |
| 34 | 09:18:13 |
| 35 | 09:18:42 |
| 36 | 09:20:33 |
| 37 | 09:20:36 |
| 38 | 09:21:04 |
| 39 | 09:21:53 |
| 40 | 09:22:23 |
| 41 | 09:22:42 |
| 42 | 09:22:51 |
| 43 | 09:28:14 |
+----+--------------------+
Desired output would be something like:
+-------+----------+
| Count | Min |
+-------+----------+
| 1 | 08:10:50 |
| 3 | 09:07:36 |
| 7 | 09:12:08 |
| 8 | 09:20:33 |
+-------+----------+
How about this:
SELECT time,
FROM (
SELECT count(*) AS c, min(time) AS time
FROM transactions
GROUP BY floor(extract(epoch from time)/600);
)
WHERE c > 10;
This will find all ten minute intervals for which more than ten transactions occurred within that interval. It assumes that the table is called transactions and that it has a column called time where the timestamp is stored.
Thanks to redneb, I ended up with the following query:
SELECT count(*) AS c, min(register_timestamp) AS register_timestamp
FROM trak_participants_data
GROUP BY floor(extract(epoch from register_timestamp)/600)
order by register_timestamp
It works close enough for me to be able tell which time chunks are the most busiest for the counter.
I would like to subtract promoters and detractors in Tableau by creating a new column. Thanks for all the help!
Customer Type Table (I would like to create the NPS field as shown below):
+---------+------------+----------+-----------+--------------+
| Quarter | Detractors | Passives | Promoters | NPS |
+---------+------------+----------+-----------+--------------+
| Q1 15 | 40.56 | 23.56 | 35.79 | =35.79-40.56 |
| ... | ... | ... | ... | ... |
+---------+------------+----------+-----------+--------------+
Simply create a calculated field (called NPS):
[Promoters] - [Detractors]
This will add a new field to every row of your partition called NPS.
Check out the Tableau online help on calculated fields - this is a skill well worth learning.
I understand the OPs question. The data comes in like this:
+---------+---------------+------+
| Quarter | Customer Type | Score|
+---------+------------+---------+
| Q1 15 | Detractors | 25 |
| Q1 15 | Promoters | 32 |
| Q1 15 | Passives | 45 |
| Q1 15 | Detractors | 17 |
| Q1 15 | Detractors | 28 |
| ... | ... | ... |
+---------+------------+---------+
And when brought into Tableau, the [Customer Type] field is put in the Column shelf and this arranges the data like the table below. The OP wants to calculate the [NPS] column (Promoters - Detractors).
+---------+------------+----------+-----------+--------------+
| Quarter | Detractors | Passives | Promoters | NPS |
+---------+------------+----------+-----------+--------------+
| Q1 15 | 40.56 | 23.56 | 35.79 | =35.79-40.56 |
| ... | ... | ... | ... | ... |
+---------+------------+----------+-----------+--------------+
I hope this clarifies. I am stuck with a similar situation (I want a column that shows the difference between 2015 and 2016):
+---------+-------+-------+------------+
| Measure | 2015 | 2016 | Difference |
+---------+---------------+------------+
| # Hires | 100 | 115 | 15 |
| # Terms | 9 | 6 | 3 |
+---------+---------------+------------+
I believe the steps are similar. I hope someone can help.