I have data something like below for the name of person and the total sales he/she made:
ABC1 34
ABC2 45
ABC3 78
ABC4 79
ABC5 23
ABC6 61
ABC7 34
ABC8 54
ABC9 90
I have to display the dashboard as below, top 3 sales guys and the overall total sales made by rest of the team as ROT which is 498 - (90 + 78 + 79) = 251 team:
ABC9 90
ABC4 79
ABC3 78
ROT 251
For the top sales made, I gave a filter by sales person name, with Limit condition as "Top 3". But I am struggling to display the ROI even in a separate worksheet. Any help is appreciated.
Right click on your dimension [Sales Guy] and choose Create/Set
Define the set by the Top N (either hard code it or use a parameter to change it easily) and call it [TopNSalesGuy]
Create a calculated field [TopNSalesGuysPlusOther] with the formular:
IF [TopNSalesGuy] THEN [Sales Guy] ELSE 'ROT' END
Use [TopNSalesGuysPlusOther] in your table/graph and you should have the top N sales guys by name and everythign else as 'ROT
Related
I have a sample dataset like below and I would like to create a report in such a format that the Value is updated for all the dates between the Start and End date.
Input Dataset
ID Start End Value
232 "2022-06-08 18:49:00" "2022-11-18 08:06:00" 55
456 "2022-10-17 10:24:00" "2022-12-16 12:52:00" 100
From the above Dataset I would like to create another dataset as below.
I need to generate the date series from the START and END date from the Input dataset and fill the same value to all of those value.
Any ideas or suggestions will be helpful.
Expected Output
ID Date Value
232 "2022-06-08" 55
232 "2022-06-09" 55
232 "2022-06-10" 55
232 "2022-06-11" 55
232 "2022-06-12" 55
.
.
232 "2022-11-17" 55
232 "2022-11-18" 55
456 "2022-10-17" 100
456 "2022-10-18" 100
456 "2022-10-19" 100
.
.
456 "2022-12-15" 100
456 "2022-12-16" 100
Database : Postgres 12
You can use generate_series()
select t.id,
g.dt::date as date,
t.value
from the_table t
cross join generate_series(t."Start"::date, t."End"::date, interval '1 day') as g(dt)
order by t.id, g.dt
I am using PostgreSQL and I am trying to calculate the percentage change for two values in the same column and group them by the name column and I am having trouble.
Suppose I have the following table:
name
day
score
Allen
1
87
Allen
2
89
Allen
3
95
Bob
1
64
Bob
2
68
Bob
3
75
Carl
1
71
Carl
2
77
Carl
3
80
I want the result to be the name and the percentage change for each person between day 3 and day 1. So Allen would be 9.2 because from 87 to 95 is a 9.2 percent increase.
I want the result to be:
name
percent_change
Allen
9.2
Bob
17.2
Carl
12.7
Thanks for your help.
Try this...
with dummy_table as (
select
name,
day,
score as first_day_score,
lag(score, 2) over (partition by name order by day desc) as last_day_score
from YOUR_TABLE_NAME
)
select
name,
(last_day_score - first_day_score) / first_day_score::decimal as percentage_change
from dummy_table where last_day_score is not null
Just replace YOUR_TABLE_NAME. There are likely more performant and fancier solutions, but this works.
You can try with lag function, something like this:
select name, day, score, 100*(score - lag(score, 1) over (partition by name order by day))/(lag(score, 1) over (partition by name order by day)) as growth_percentage
I am new to KDB and cannot understand why i can access the order column for the table stocks but not trader. The below is my code with the error.
q)trader
item brand | price order
---------------| -----------
soda fry | 1.5 200
bacon prok | 1.99 180
mushroom veggie| 0.88 110
eggs veggie| 1.55 210
tomatoes veggie| 1.35 100
q)trader.order
'order
[0] trader.order
^
q)stock.order
50 82 45 92
q)stock
item brand price order
---------------------------
soda fry 1.5 50
bacon prok 1.99 82
mushroom veggie 0.88 45
eggs veggie 1.55 92
q)trader.order
'order
[0] trader.order
^
Your table trader is keyed and you cannot use trader.order to select the order column.
You can use this instead if you want
(0!trader)`order
The reason is because when you do trader.order what you actually do is you use indexing. It's the same as if you'd do list.index. A table is just a list of dictionaries and you use dot(.) to index into it. However a keyed table does not have the same structure so you'll have to unkey it first.
I'm new to KDB/Q and have a question around getting the difference between two (not necessarily adjacent) rows.
I have only one table, which looks like the below:
q)tickers:`ibm`bac`dis`gs`ibm`gs`dis`bac
q)pxs:100 50 30 250 110 240 45 48
q)dates:2013.05.01 2013.01.05 2013.02.03 2013.02.11 2013.06.17 2013.06.21 2013.04.24 2013.01.06
q)trades:([tickers;dates];pxs)
q)trades
tickers dates | pxs
------------------| ---
ibm 2013.05.01| 100
bac 2013.01.05| 50
dis 2013.02.03| 30
gs 2013.02.11| 250
ibm 2013.06.17| 110
gs 2013.06.21| 240
dis 2013.04.24| 45
bac 2013.01.06| 48
I would like to be able to have a either another column in the table that stores the difference between the current and the previous price, or another structure similar in structure. The key question that the resulting needs to answer is "by how much did the stock change compared to the previous time a price was recorded?"
So far I've tried something along the lines of:
select tickers, dates, pxs - pxs(dates bin (exec dates from trades where tickers = trades.tickers)) from trades
which doesn't really work (at all). Definitely due to trying to do SQL-like queries and having a row-oriented mindset.
Please find below an exemple of the sought after answer:
q)trades: do magic with trades
q)trades
tickers dates | pxs | delta
------------------| --- | -----
ibm 2013.05.01| 100 | 0
bac 2013.01.05| 50 | 0
dis 2013.02.03| 30 | 0
gs 2013.02.11| 250 | 0
ibm 2013.06.17| 110 | 10
gs 2013.06.21| 240 | -10
dis 2013.04.24| 45 | 15
bac 2013.01.06| 48 | -2
Thanks for your help,
Dan
q)update delta:{0,1_deltas x}pxs by tickers from trades
tickers dates | pxs delta
------------------| ---------
ibm 2013.05.01| 100 0
bac 2013.01.05| 50 0
dis 2013.02.03| 30 0
gs 2013.02.11| 250 0
ibm 2013.06.17| 110 10
gs 2013.06.21| 240 -10
dis 2013.04.24| 45 15
bac 2013.01.06| 48 -2
if you do:
select pxs by dates,tickers from table
you will have a complex column (pxs) which is a list of prices for the particular date and ticker. You can then apply deltas:
select deltas pxs by dates,tickers from table
Which will give you the running difference. The first value is the original pxs though so you'll need to update the first one to 0.
EDIT
Just re-read and having looked at your result, you'll need to join back to your original trade table
update dates, pxs, delta:(0N,(-1_ pxs) - 1_ pxs) by tickers from trades
Please find how it works:
select pxs by tickets from trades
creates table which rows contains: ticket and list pxs.
So in every row we have a list:
tickers| pxs
-------| -------
bac | 50 48
dis | 30 45
gs | 250 240
ibm | 100 110
now we have to apply function which will calculate delta. Best function mentioned above: deltas, but my version is about the same.
if we select - then we will have table with tickers|list of pxs|list of deltas, but is we use update .. by, then it ungroup groupped values.
You can get the same results using the prev function. One thing worth highlighting that prev automatically adds the null (0N) as the first element. This is important as we don't have the previous information available, however, adding a 0 as the first element suggests that there has not been any change; though it depends on how you want to handle the first record.
q)update delta:pxs-prev[pxs] by tickers from trades
tickers dates | pxs delta
------------------| ---------
ibm 2013.05.01| 100
bac 2013.01.05| 50
dis 2013.02.03| 30
gs 2013.02.11| 250
ibm 2013.06.17| 110 10
gs 2013.06.21| 240 -10
dis 2013.04.24| 45 15
bac 2013.01.06| 48 -2
using deltas to get the same results (0N instead of 0)
q)update delta:{0N,1_deltas x}pxs by tickers from trades
I'm working in Crystal Report 2008, And I have a data with like this:
Date KG MT SQM
--------------------------------------------
01-01-2013 25000 25
01-01-2013 15000 15
01-01-2013 15000 15 -----(duplicated)
01-02-2013 13000 13
01-02-2013 12000 12
01-03-2013 18000 18
01-03-2013 33000 33
Then I tried to group it by date so the output is like this: so it's already removed the duplicated and sum the vlaue without a problem.
Date KG MT SQM
--------------------------------------------
01-01-2013 40000 40 55000
01-02-2013 25000 25 25000
01-03-2013 51000 51 51000
TOTAL 116,000 116 131,000
Then I want to add the SQM, and when I sum it, it will sum all the record in the group also with duplicated record.
(if you will sum the 3rd field, it also included in sum the duplicated record should be only '116,000' and not '131,000')
My question, how can I suppressed if duplicated and at the same time it will give me summary of the group to show the correct value?
Thanks,
Captain16