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?
Related
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
I want to calculate average in Spotfire only when there are minimum 3 values. if there are no values or just 2 values the average should be blank
Raw data:
Product Age Average
1
2
3 10
4 12
5 13 11
6
7 18
8 19
9 20 19
10 21 20
The only way I could really do this is with 3 calculated columns. Insert these calculated columns in this order:
If(Min(If([Age] IS NULL,0,[Age])) over (LastPeriods(3,[Product]))<>0,1) as [BitFlag]
Avg([Age]) over (LastPeriods(3,[Product])) as [TempAvg]
If([BitFlag]=1,[TempAvg]) as [Average]
This will give you the following results. You can ignore / hide the two columns you don't care about.
RESULTS
+---------+-----+---------+------------------+------------------+
| Product | Age | BitFlag | TempAvg | Average |
+---------+-----+---------+------------------+------------------+
| 1 | | | | |
| 2 | | | | |
| 3 | 10 | | 10 | |
| 4 | 12 | | 11 | |
| 5 | 13 | 1 | 11.6666666666667 | 11.6666666666667 |
| 6 | | | 12.5 | |
| 7 | 18 | | 15.5 | |
| 8 | 19 | | 18.5 | |
| 9 | 20 | 1 | 19 | 19 |
| 10 | 21 | 1 | 20 | 20 |
| 11 | | | 20.5 | |
| 12 | 22 | | 21.5 | |
| 13 | 36 | | 29 | |
| 14 | | | 29 | |
| 15 | 11 | | 23.5 | |
| 16 | 23 | | 17 | |
| 17 | 14 | 1 | 16 | 16 |
+---------+-----+---------+------------------+------------------+
Now I need 5 formula for sum of each column, it works fine but I wish it can be simplified to one formula. Is it possible?
|----+----+----+-----+----|
| a | b | c | d | e |
|----+----+----+-----+----|
| 1 | 2 | 3 | 4 | 5 |
| 6 | 7 | 8 | 9 | 10 |
| 11 | 12 | 13 | 14 | 15 |
| 16 | 17 | 18 | 19 | 20 |
|----+----+----+-----+----|
| 34 | 38 | 42 | 160 | 50 |
|----+----+----+-----+----|
#+TBLFM: #>$5=vsum(#2$5..#-1$5)::#>$4=vsum(#2$1..#-1$4)::#>$3=vsum(#2$3..#-1$3)::#>$2=vsum(#2$2..#-1$2)::#>$1=vsum(#2$1..#-1$1)
This should work:
|----+----+----+----+----|
| a | b | c | d | e |
|----+----+----+----+----|
| 1 | 2 | 3 | 4 | 5 |
| 6 | 7 | 8 | 9 | 10 |
| 11 | 12 | 13 | 14 | 15 |
| 16 | 17 | 18 | 19 | 20 |
|----+----+----+----+----|
| 34 | 38 | 42 | 46 | 50 |
|----+----+----+----+----|
#+TBLFM: #>$1..#>$5=vsum(#2$0..#-1$0)
$0 on the RHS is the current column.
I am using postgresql and I have a table called accidents (state, total accidents) and another table called population. I want to get the top 3 state names with high total accidents and then get the population of those 3 states divided by total accidents in postgresql? How to write the query in the following way?
Explanation:
Population Table
rank| state | population
---+-----------------------------+------------
1 | Uttar Pradesh | 199581477
2 | Maharashtra | 112372972
3 | Bihar | 103804630
4 | West Bengal | 91347736
5 | Madhya Pradesh | 72597565
6 | Tamil Nadu | 72138958
7 | Rajasthan | 68621012
8 | Karnataka | 61130704
9 | Gujarat | 60383628
10 | Andhra Pradesh | 49665533
11 | Odisha | 41947358
12 | Telangana | 35193978
13 | Kerala | 33387677
14 | Jharkhand | 32966238
15 | Assam | 31169272
16 | Punjab | 27704236
17 | Haryana | 25753081
18 | Chhattisgarh | 25540196
19 | Jammu and Kashmir | 12548926
20 | Uttarakhand | 10116752
21 | Himachal Pradesh | 6856509
22 | Tripura | 3671032
23 | Meghalaya | 2964007
24 | Manipur*β* | 2721756
25 | Nagaland | 1980602
26 | Goa | 1457723
27 | Arunachal Pradesh | 1382611
28 | Mizoram | 1091014
29 | Sikkim | 607688
30 | Delhi | 16753235
31 | Puducherry | 1244464
32 | Chandigarh | 1054686
33 | Andaman and Nicobar Islands | 379944
34 | Dadra and Nagar Haveli | 342853
35 | Daman and Diu | 242911
36 | Lakshadweep | 64429
accident table:
state | eqto8 | eqto10 | mrthn10 | ntknwn | total
-----------------------------+-------+--------+---------+--------+--------
Andhra Pradesh | 6425 | 8657 | 8144 | 19298 | 42524
Arunachal Pradesh | 88 | 76 | 87 | 0 | 251
Assam | 0 | 0 | 0 | 6535 | 6535
Bihar | 2660 | 3938 | 3722 | 0 | 10320
Chhattisgarh | 2888 | 7052 | 3571 | 0 | 13511
Goa | 616 | 1512 | 2184 | 0 | 4312
Gujarat | 4864 | 7864 | 7132 | 8089 | 27949
Haryana | 3365 | 2588 | 4112 | 0 | 10065
Himachal Pradesh | 276 | 626 | 977 | 1020 | 2899
Jammu and Kashmir | 1557 | 618 | 434 | 4100 | 6709
Jharkhand | 1128 | 701 | 1037 | 2845 | 5711
Karnataka | 11167 | 14715 | 18566 | 0 | 44448
Kerala | 5580 | 13271 | 17323 | 0 | 36174
Madhya Pradesh | 15630 | 16226 | 19354 | 0 | 51210
Maharashtra | 4117 | 5350 | 10538 | 46311 | 66316
Manipur | 147 | 453 | 171 | 0 | 771
Meghalaya | 210 | 154 | 119 | 0 | 483
Mizoram | 27 | 58 | 25 | 0 | 110
Nagaland | 11 | 13 | 18 | 0 | 42
Odisha | 1881 | 3120 | 4284 | 0 | 9285
Punjab | 1378 | 2231 | 1825 | 907 | 6341
Rajasthan | 5534 | 5895 | 5475 | 6065 | 22969
Sikkim | 6 | 144 | 8 | 0 | 158
Tamil Nadu | 8424 | 18826 | 29871 | 10636 | 67757
Tripura | 290 | 376 | 222 | 0 | 888
Uttarakhand | 318 | 305 | 456 | 393 | 1472
Uttar Pradesh | 8520 | 10457 | 10995 | 0 | 29972
West Bengal | 1494 | 1311 | 974 | 8511 | 12290
Andaman and Nicobar Islands | 18 | 104 | 114 | 0 | 236
Chandigarh | 112 | 39 | 210 | 58 | 419
Dadra and Nagar Haveli | 40 | 20 | 17 | 8 | 85
Daman and Diu | 11 | 6 | 8 | 25 | 50
Delhi | 0 | 0 | 0 | 6937 | 6937
Lakshadweep | 0 | 0 | 0 | 3 | 3
Puducherry | 154 | 668 | 359 | 0 | 1181
All India | 88936 | 127374 | 152332 | 121741 | 490383
So that result should be
21.57
81.03
107.44
explanation:
Highest accidents states Tamilnadu, Maharashtra, Madhyapradesh.
Tamilnadu population/accidents = 21213/983 = 21.57 (Assumed values)
Maharasthra population/accidents = 10000/123 = 81.03
Madhyapradesh population/accidents = 34812/324 = 107.44
My query is:
SELECT POPULATION/
(SELECT TOTAL
FROM accidents
WHERE STATE NOT LIKE 'All %'
ORDER BY TOTAL DESC
LIMIT 3)
aVG FROM population
WHERE STATE IN
(SELECT STATE
FROM accidents
WHERE STATE NOT LIKE 'All %'
ORDER BY TOTAL DESC
LIMIT 3);
throwing ERROR: more than one row returned by a subquery used as an expression.
How to modify the query to get the required result or any other way to get the result in postgresql?
This ought to do it.
SELECT a.state, population.population/a.total FROM
(SELECT total, state FROM accidents WHERE state <> 'All India' ORDER BY total DESC LIMIT 3 ) AS a
INNER JOIN population on a.state = population.state
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.