I am new to Tableau and I have requirements as below:
I need to create a dashboard with a filter on Paywave or EMV and show count of Confirmed and Probable on a geo map.
When I select EMV from the quick filter, it should show a count of confirm & probable for that city. I should be able to drill down and see a count of confirm and probable for zip codes as well.
I am not sure how to achieve the above requirements.
As shown below I have fields like:
EMV Paywave
mrchchant_city, mrch_zipcode confirm probable confirm probable
A 1001 10 15 20 18
B 1005 34 67 78 12
C 2001 24 56 76 45
C 2001 46 19 63 25
Please let me know if any information required from my side.
This will be a lot easier on you if you restructure your data a bit. More often than not, the goal in Tableau is to provide an aggregated summary of the data, rather than showing each individual row. We'll want to group by dimensions (categorical data like "EMV"/"Paywave" or "Confirm"/"Probable"), so this data will be much easier to work with if we get those dimensions into their own columns.
Here's how I personally would go about structuring your table:
+----------------+--------------+---------+----------+-------+-----+
| mrchchant_city | mrch_zipcode | dim1 | dim2 | count | ... |
+----------------+--------------+---------+----------+-------+-----+
| A | 1001 | Paywave | confirm | 20 | ... |
| A | 1001 | Paywave | probable | 18 | ... |
| A | 1001 | EMV | confirm | 10 | ... |
| A | 1001 | EMV | probable | 15 | ... |
| B | 1005 | Paywave | confirm | 78 | ... |
| B | 1005 | Paywave | probable | 12 | ... |
| B | 1005 | EMV | confirm | 34 | ... |
| B | 1005 | EMV | probable | 67 | ... |
| C | 2001 | Paywave | confirm | 76 | ... |
| C | 2001 | Paywave | probable | 45 | ... |
| C | 2001 | EMV | confirm | 24 | ... |
| C | 2001 | EMV | probable | 56 | ... |
| C | 2001 | Paywave | confirm | 63 | ... |
| C | 2001 | Paywave | probable | 25 | ... |
| C | 2001 | EMV | confirm | 46 | ... |
| C | 2001 | EMV | probable | 19 | ... |
| ... | ... | ... | ... | ... | ... |
+----------------+--------------+---------+----------+-------+-----+
(Sorry about the dim1 and dim2, I don't really know what those dimensions represent. You can/should obviously pick a more intuitive nomenclature.)
Once you have a table with columns for your categorical data, it will be simple to filter and group by those dimensions.
Related
Please help me make a request. i'm at a dead end.
There are 2 tables:
“Trains”:
+----+---------+
| id | numbers |
+----+---------+
| 1 | 101 |
| 2 | 102 |
| 3 | 103 |
| 4 | 104 |
| 5 | 105 |
+----+---------+
“Passages”:
+----+--------------+-------+---------------------+
| id | train_number | speed | date_time |
+----+--------------+-------+---------------------+
| 1 | 101 | 26 | 2021-11-10 16:26:30 |
| 2 | 101 | 28 | 2021-11-12 16:26:30 |
| 3 | 102 | 24 | 2021-11-14 16:26:30 |
| 4 | 103 | 27 | 2021-11-15 16:26:30 |
| 5 | 101 | 29 | 2021-11-16 16:26:30 |
+----+--------------+-------+---------------------+
The goal is to go through the train numbers from the Trains table, take from the existing ones from the Passages table by the latest date (date_time) and the number of passages for “the last date for each train” - N days. as I understand date_time - interval "N days". should get something like:
+----+--------+---------------------+----------------+
| id | train | last_passage | count_passages |
+----+--------+---------------------+----------------+
| 1 | 101 | 2021-11-10 16:26:30 | 2 |
| 2 | 102 | 2021-11-14 16:26:30 | 1 |
| 3 | 103 | 2021-11-15 16:26:30 | 1 |
| 4 | 104 | null | 0 |
| 5 | 105 | null | 0 |
+----+--------+---------------------+----------------+
ps: "count_passages" - for example, last passage date minus 4 days
I tried through "where in" but I can’t create the necessary and correct request
I am having a hard time trying to wrap my head around the pivot/unpivot concepts and hoping someone can help or give me some guidance on how to approach my problem.
Here is a simplified sample table I have
+-------+------+------+------+------+------+
| SAUID | COM1 | COM2 | COM3 | COM4 | COM5 |
+-------+------+------+------+------+------+
| 1 | 24 | 22 | 100 | 0 | 45 |
| 2 | 34 | 55 | 789 | 23 | 0 |
| 3 | 33 | 99 | 5552 | 35 | 4675 |
+-------+------+------+------+------+------+
The end result I am looking for a table result similar below
+-------+-----------+-------+
| SAUID | OCCUPANCY | VALUE |
+-------+-----------+-------+
| 1 | COM1 | 24 |
| 1 | COM2 | 22 |
| 1 | COM3 | 100 |
| 1 | COM4 | 0 |
| 1 | COM5 | 45 |
| 2 | COM1 | 34 |
| 2 | COM2 | 55 |
| 2 | COM3 | 789 |
| 2 | COM4 | 23 |
| 2 | COM5 | 0 |
| 3 | COM1 | 33 |
| 3 | COM2 | 99 |
| 3 | COM3 | 5552 |
| 3 | COM4 | 35 |
| 3 | COM5 | 4675 |
+-------+-----------+-------+
Im looking around but most of the examples seem to use pivot but having a hard time trying to wrap that around my case as I need the values all in one column.
I hoping to experiment with some hardcoding to get fimilar with my example but my actual table columns are ~100 with varying #s of SAUID per table and looks like it will require dynamic sql?
Thanks for the help in advance.
Use UNPIVOT:
SELECT u.SAUID, u.OCCUPANCY, u.VALUE
FROM yourTable t
UNPIVOT
(
VALUE for OCCUPANCY in (COM1, COM2, COM3, COM4, COM5)
) u;
ORDER BY
u.SAUID, u.OCCUPANCY;
Demo
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'm working with Jaspersoft Studio.
I've a crosstab similar to this one:
+---------+------+------+
| FRUIT | 2014 | 2015 |
+---------+------+------+
| apples | 12 | 85 |
+---------+------+------+
| peaches | 74 | 36 |
+---------+------+------+
| bananas | 54 | 82 |
+---------+------+------+
and I would like to obtain something like this:
+---------+------+------+---------------------+
| FRUIT | 2014 | 2015 | Difference |
| | | | between 2015/2014 |
| | | | (delta) |
+---------+------+------+---------------------+
| apples | 12 | 85 | 73 |
+---------+------+------+---------------------+
| peaches | 74 | 36 | -38 |
+---------+------+------+---------------------+
| bananas | 54 | 82 | 28 |
+---------+------+------+---------------------+
Is it possible?
I mean, it's there a way to intercetpt the value of a field in the single period (e.g. 2014) and use it for a custom calculation?
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.