I have a table cash_drawer which stores quantity for each denomination of currency for each day at day end:
cash_drawer(
date DATE,
100 SMALLINT,
50 SMALLINT,
20 SMALLINT,
10 SMALLINT,
5 SMALLINT,
1 SMALLINT
)
Now any given day, I wish to get each denomination as a row.
If lets say for day 2016-11-25, if we have the following row:
+------------+-------+------+------+------+-----+-----+
| date | 100 | 50 | 20 | 10 | 5 | 1 |
+------------+-------+------+------+------+-----+-----+
| 2016-11-25 | 5 | 12 | 27 | 43 | 147 | 129 |
+------------+-------+------+------+------+-----+-----+
Now I wish to get the out put of the query as:
+------------+--------+
|denomination|quantity|
+------------+--------+
|100 |5 |
+------------+--------+
|50 |12 |
+------------+--------+
|20 |27 |
+------------+--------+
|10 |43 |
+------------+--------+
|5 |147 |
+------------+--------+
|1 |129 |
+------------+--------+
Is there a method by which this is possible? If you have any other suggestion please be free to suggest.
Use json functions:
select key as denomination, value as quantity
from cash_drawer c,
lateral json_each(row_to_json(c))
where key <> 'date'
and date = '2016-11-25';
denomination | quantity
--------------+----------
100 | 5
50 | 12
20 | 27
10 | 43
5 | 147
1 | 129
(6 rows)
Test it here.
Related
I have a problem with pivot tables ....
I don't understand what to do ...
My table is as follows:
|CODART|MONTH|QT |
|------|-----|----|
|ART1 |1 |100 |
|ART2 |1 |30 |
|ART3 |1 |30 |
|ART1 |2 |10 |
|ART4 |2 |40 |
|ART3 |4 |50 |
|ART5 |4 |60 |
I would like to get a summary table by month:
|CODART|1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |
|------|---|---|---|---|---|---|---|---|---|---|---|---|
|ART1 |100|10 | | | | | | | | | | |
|ART2 |30 | | | | | | | | | | | |
|ART3 |30 | | |50 | | | | | | | | |
|ART4 | |2 | | | | | | | | | | |
|ART5 | | | |60 | | | | | | | | |
|TOTAL |160|12 | |110| | | | | | | | |
Too many requests? :-)
Thanks for the support
WITH MYTAB (CODART, MONTH, QT) AS
(
VALUES
('ART1', 1, 100)
, ('ART2', 1, 30)
, ('ART3', 1, 30)
, ('ART1', 2, 10)
, ('ART4', 2, 40)
, ('ART3', 4, 50)
, ('ART5', 4, 60)
)
SELECT
CASE GROUPING (CODART) WHEN 0 THEN CODART ELSE 'TOTAL' END AS CODART
, SUM (CASE MONTH WHEN 1 THEN QT END) AS "1"
, SUM (CASE MONTH WHEN 2 THEN QT END) AS "2"
, SUM (CASE MONTH WHEN 3 THEN QT END) AS "3"
, SUM (CASE MONTH WHEN 4 THEN QT END) AS "4"
---
, SUM (CASE MONTH WHEN 12 THEN QT END) AS "12"
FROM MYTAB T
GROUP BY ROLLUP (T.CODART)
ORDER BY GROUPING (T.CODART), T.CODART
CODART
1
2
3
4
12
ART1
100
10
ART2
30
ART3
30
50
ART4
40
ART5
60
TOTAL
160
50
110
Let's say we have
|bin | min | end | start |
|1 | 5 | 10 |
|2 | 12 | 24 |
|3 | 28 | 36 |
|4 | 40 | 50 |
|5 | null| null |
I would want to populate start as the previous column's end to make continuous bin values. For the missing I would like to fill in with the current min instead. For null row I consider treating it separately.
What lag gives us would be
df.withColumn("start", F.lag(col("end"), 1, ***default_value***).over(orderBy(col("bin"))
|bin | min | end | start |
|1 | 5 | 10 | (5 wanted)
|2 | 12 | 24 | 10
|3 | 28 | 36 | 24
|4 | 40 | 50 | 36
|5 | null| null | null
My questions :
1/ What do we put in default_value for lag to take another column of current row, in this case min
2/ Is there a way to treat null row at the same time without separating ? I intend to filter non-null , perform lag, then union back with the null rows. How will the answer differ if Null is the first(bin 1) or last (bin 5) ?
Use coalesce to get a column value for the first row in a group.
from pyspark.sql import functions as F
df.withColumn("start", F.coalesce(F.lag(col("end"), 1).over(orderBy(col("bin")),col("min")))
lag currently doesn't support ignorenulls option, so you might have to separate out the null rows, compute the start column for non-null rows and union the data frames.
I have a table which contains transaction dates and the balances of those transactions. Example Below:
select id, transaction_bal1, transaction_bal2, transaction_date
from transactions
Which results in
ID | transaction_bal1 | transaction_bal2 | transaction_date
1 | -10000 | 1000 | 2017.01.02
2 | 4000 | 1000 | 2017.02.02
3 | 4000 | 1000 | 2017.03.02
etc...
What I want to do is to generate a series with '1 day'::interval so that I select all days between the transaciton dates and that the rows in the above table falls under the right day. Something like this:
Gen_series | ID | transaction 1 | transaction 2 | transaction_date
2017.01.01 |null| 0 | 0 | null
2017.01.02 |1 | -10000 | 1000 | 2017.01.02
2017.01.03 |null| 0 | 0 | null
...
2017.02.01 |null| 0 | 0 | null
2017.02.02 |1 | 4000 | 1000 | 2017.01.02
2017.02.03 |null| 0 | 0 | null
etc...
I use Postgresql(dont know which version) but I use PgAdmin 4 3.2 (if that is of any help)
Feel free to ask any questions if I need to flesh out anything.
I have a PostgreSQL 9.1 database with a table containing measurement data, which contains setpoint information. For example temperature setpoints. The measurements are taken when at a setpoint, after which the following setpoint will be set. A setpoint can be reached multiple times, e.g. -25, 25, 75, 125, 75, 25 degree Celcius. In this case 25 and 75 degree Celcius are reached multiple times.
Now I want to group the data per setpoint, but not group data together of another setpoint that has the same value but is reached at a later point in time.
Example data:
| id | setpoint | value |<dyn.group>|
| 1 | -25 | 5.324 | 1
| 2 | -25 | 6.343 | 1
| 3 | -25 | 6.432 | 1
| 4 | 25 | 3.432 | 2
| 5 | 25 | 4.472 | 2
| 6 | 25 | 6.221 | 2
| 7 | 75 | 5.142 | 3
| 8 | 75 | 7.922 | 3
| 9 | 75 | 3.832 | 3
|10 | 125 | 8.882 | 4
|11 | 125 | 9.742 | 4
|12 | 125 | 7.632 | 4
|13 | 75 | 5.542 | 5
|14 | 75 | 2.452 | 5
|15 | 75 | 1.332 | 5
|16 | 25 | 3.232 | 6
|17 | 25 | 4.132 | 6
|18 | 25 | 5.432 | 6
Normal group by clauses will fail, because setpoint can be there multiple times, but should not be put together.
Looking with LEAD and LAG to the previous/next values is also not desired, because changes will most likely be similar (e.g. if setpoint 75 is repeated, then most likely the step from 25->75 will also be repeated).
The expected outcome is the 4th column (<dyn.group>). With that column I can for example average on these groups.
It can be done with a custom aggregation function to generate the "group index" value and then a "group by" clause in that value.
I have following table:
|Type | Year | amount |
_______________________
|t1 | 2001 | 40 |
|t1 | 2000 | 50 |
|t2 | 2003 | 30 |
|t2 | 2003 | 20 |
|t3 | 2004 | 10 |
and I would like to show it as:
| type |2001 |2000 |2003 |2004|
|______________________________
| t1 |40 |50 |0 |0 |
| t2 | 0 |0 | 50 |0 |
| t3 |0 |0 | 0 |10 |
I don't want to hard code the years and I need to do that in POstgresql 8.4, which doesn't support:
CREATE EXTENSION
IF NOT EXISTS tablefunc;
I have pivoted table before, using following code: more explanation for the following code is here
sum(CASE
WHEN year = 2000 THEN
total
ELSE 0
END)
In which the total =sum (amount) in each year and I had calculated it in another CTE. But at that time the years were already known but for the above table I need to loop through the years and read each and then calculate the sum(amount) and the years may change in the main table.