I am new to react and Ag-Grid as well, I need to have two columns, Column-A and Column-B. In Column-A it should be text-box and Column-B should be a dropdown where the list of values are from Column-A, if the entered value is not present in Column-A a new row should be added,
ex:
Column-A | Column-B
10 | 10
20 | 10
30 | 20
40 | 70
Now in the above table for Column-B I have entered value as 70, but in Column-A the value 70 does not exist, hence it should create a new row with Column-A having value as 70 and leaving Column-B as empty, like below.
Column-A | Column-B
10 | 10
20 | 10
30 | 20
40 | 70
70 |
I did not got any idea for creating this functionality, please help me on this.
Related
I have a query which returns results of data, which runs on a frequent basis. The new table will contain results of the old table as well but I only want to take whatever is in new in the most recent run of the new table and send that as an email. I already have the line for the email and trade data but just need a way to be able to:
display the results of the new table to be emailed
save the complete results of the new table to be used in the next run of the query
e.g.
Old results: tbl
| idx | name | age |
| 0 | Tom | 30 |
| 1 | Jerry | 25 |
| 2 | Bob | 30 |
| 3 | Ken | 45 |
New results: tbl
| idx | name | age |
| 0 | Tom | 30 |
| 1 | Jerry | 25 |
| 2 | Bob | 30 |
| 3 | Ken | 45 |
| 4 | Sam | 40 |
output required:
| 4 | Sam | 40 |
and then save the New results to be used in the next run
Thanks! :)
If the only changes between runs is that records are being appended onto the new table, you could just keep a variable denoting the last index seen and then select only those rows where idx is larger than that.
If the indexes are always increasing, this could be achieved using a query like
lastidx:exec last idx from tbl
select from tbl where idx>lastidx
If the idx values don't always increase monotonically, you could keep a count of the number of rows instead and only
lasti:count tbl
select from tbl where i>=lasti
This doesn't require saving the whole table in memory for use in the next iteration.
E.g to start with the old table had 4 rows so lasti = 4
q)tbl
idx name age
-------------
0 Tom 30
1 Jerry 25
2 Bob 30
3 Ken 45
q)lasti
4
The new table comes in and running the command selects the new row
q)tbl
idx name age
-------------
0 Tom 30
1 Jerry 25
2 Bob 30
3 Ken 45
4 Sam 40
q)select from tbl where i>lasti
idx name age
------------
4 Sam 40
lasti can then be updated to reflect the new count
q)lasti:count tbl
q)lasti
5
One way you can get this done, assuming the idx is the unique key :
q)old:([] idx:0 1 2 3; name:`T`J`B`K; age: 30 25 30 45)
q)new:old,enlist `idx`name`age!(4; `S;40) //new output from your query
q)out:()
q)if[0<count i:new[`idx] except old[`idx] ; out:new i ; old:new]
q)out
idx name age
------------
4 S 40
Another way, if your new records are always added to the last of old records:
q)old:([] idx:0 1 2 3; name:`T`J`B`K; age: 30 25 30 45)
q)i:count old
q)new:old,enlist `idx`name`age!(4; `S;40) //new output from your query
q)out:()
q)if[i<c:count new ; out:(i-c)#new ; old:new; i:c]
q)out
idx name age
------------
4 S 40
Let's assume I have a table with a counter column where all new rows has an equal or larger counter integer value. For example a proper table could like this:
id | counter
-------------
1 | 0
2 | 1
3 | 3
4 | 3
5 | 4
6 | 7
7 | 11
8 | 19
9 | 19
10 | 120
11 | 124
12 | 133
However let's assume some odd rows are inserted that breaks the rule like in this example with 2 NOT good rows :
id | counter
-------------
1 | 0 (first row)
2 | 1 (larger value, good)
3 | 3 (larger value, good)
4 | 3 (same value, good)
5 | 4 (larger value, good)
6 | 21 (larger value, it appears to be good at this point, however next values proves this was an actually an error, *NOT good*, should be removed from the result sets)
7 | 11 (smaller value, it appears to be NOT good at this point, however next values proves this was NOT an error, should NOT be removed from the result sets)
8 | 19 (larger value, good)
9 | 19 (same value, good)
10 | 120 (larger value, good)
11 | 64 (smaller value, *NOT good*)
12 | 133 (larger value, good)
Would it be possible filter/discard those NOT good rows from result sets?
I am using Greenplum, and I have data like:
id | val
----+-----
12 | 12
12 | 23
12 | 34
13 | 23
13 | 34
13 | 45
(6 rows)
somehow I want the result like:
id | step
----+-----
12 | 12
12 | 11
12 | 11
13 | 23
13 | 11
13 | 11
(6 rows)
How it comes:
First there should be a Window function, which execute a de-aggreagte function based on partition by id
the column val is cumulative value, and what I want to get is the step values.
Maybe I can do it like:
select deagg(val) over (partition by id) from table_name;
So I need the deagg function.
Thanks for your help!
P.S and Greenplum is based on postgresql v8.2
You can just use the LAG function:
SELECT id,
val - lag(val, 1, 0) over (partition BY id ORDER BY val) as step
FROM yourTable
Note carefully that lag() has three parameters. The first is the column for which to find the lag, the second indicates to look at the previous record, and the third will cause lag to return a default value of zero.
Here is a table showing the table this query would generate:
id | val | lag(val, 1, 0) | val - lag(val, 1, 0)
----+-----+----------------+----------------------
12 | 12 | 0 | 12
12 | 23 | 12 | 11
12 | 34 | 23 | 11
13 | 23 | 0 | 23
13 | 34 | 23 | 11
13 | 45 | 34 | 11
Second note: This answer assumes that you want to compute your rolling difference in order of val ascending. If you want a different order you can change the ORDER BY clause of the partition.
val seems to be a cumulative sum. You can "unaggregate" it by subtracting the previous val from the current val, e.g., by using the lag function. Just note you'll have to treat the first value in each group specially, as lag will return null:
SELECT id, val - COALESCE(LAG(val) OVER (PARTITION BY id ORDER BY val), 0) AS val
FROM mytable;
I'm working with a gigantic dataset of individuals with demographic information and action tracking. I am trying to get the percentage of people who committed an action, which is simple, but also trying to get average ages of people who fit in a specific subgroup of the original SELECT. The CASE WHEN line works fine alone, and the subquery runs fine in it's own query but I cannot seem to get it integrated into this query as a subquery, it gives me a syntax error on the CASE WHEN statement. Here's a slightly anonymized version of the query. Any help would be VERY appreciated.
SELECT
AVG(ageagg)
FROM
(
SELECT
age AS ageagg
FROM
agetable
WHERE
age>30
AND action_taken=1) AvgAge_30Action,
COUNT(
CASE
WHEN action_taken=1
AND age> 30
THEN 1
ELSE 0 NULL) / COUNT(
CASE
WHEN age>30) AS Over_30_Action
FROM
agetable
WHERE
website_type=3
If I've interpreted your intent correctly, you wish to compute the following:
1) the number of people over the age of 30 that took a specific action as a percentage of the total number of people over the age of 30
2) the average age of the people over the age of 30 that took a specific action
Assuming my interpretation is correct, this query might work for you:
SELECT
100 * over_30_action / over_30_total AS percentage_of_over_30_took_action,
average_age_of_over_30_took_action
FROM (
SELECT
SUM(CASE WHEN action_taken=1 THEN 1 ELSE 0 END) AS over_30_action,
COUNT(*) AS over_30_total,
AVG(CASE WHEN action_taken=1 THEN age ELSE NULL END)
AS average_age_of_over_30_took_action
FROM agetable
WHERE website_type=3 AND age>30
) aggregated;
I created a dummy table and populated it with the following data.
postgres=# select * from agetable order by website_type, action_taken, age;
age | action_taken | website_type
-----+--------------+--------------
33 | 1 | 1
32 | 1 | 2
28 | 1 | 3
29 | 1 | 3
32 | 1 | 3
33 | 1 | 3
34 | 1 | 3
32 | 2 | 3
32 | 3 | 3
33 | 4 | 3
34 | 5 | 3
33 | 6 | 3
34 | 7 | 3
35 | 8 | 3
(14 rows)
Of the 14 rows, 4 rows (the first four in this listing) have either the wrong website_type or have age below 30. Of the ten remaining rows, you can see that 3 of them have an action_taken of 1. So, the query should determine that 30% of folks over the age of 30 took a particular action, and the average age among that particular population should be 33 (ages 32, 33, and 34). The results of the query I posted:
percentage_of_over_30_took_action | average_age_of_over_30_took_action
-----------------------------------+------------------------------------
30 | 33.0000000000000000
(1 row)
Again, all of this is predicated upon my interpretation of your intent actually being accurate. This is of course based on a highly contrived data set, but hopefully it's enough of a functional signpost to get you on the right path.
I'm trying to figure out how to show distinct records in groups in crystal reports. The view I wrote returns something like this:
Field 1 | Field 2 | Field 3
----------------------------------
10 | 111 | Record Info 1
10 | 111 | Record Info 1
10 | 222 | Record Info 2
20 | 111 | Record Info 1
20 | 222 | Record Info 2
The report groups are based off field one, and I want distinct fields 2 and 3 for each group:
Field 1 | Field 2 | Field 3
----------------------------------
10 | 111 | Record Info 1
10 | 222 | Record Info 2
20 | 111 | Record Info 1
20 | 222 | Record Info 2
Field 2 and 3 are always the same, Field 1 acts as an FK reference to any entries in the view. Selecting distinct xxx in the view isn't really viable due to the huge amount of columns being brought in.
Can this be done in CR?
Cheers
Create a group for field1, field2
Hide Details area, field1 group area header and field1 group footer
Drop all the columns you want to show in the field2 group area header/footer.
Good luck!
You might also consider using Database | Select Distinct Records.