I have a sql query that results in a table similar to the following after grouping by name, quarter, year and ordering by year DESC, quarter DESC:
name
count
quarter
year
orange
22
4
2022
apple
1
4
2022
banana
123
3
2022
pie
93
2
2022
apple
12
2
2022
orange
0
1
2022
apple
900
4
2021
...
...
...
...
I want to remove any rows that come after the 4th unique combination of quarter and year is reached (for the table above this would be any rows after the last combination of quarter 1, year 2022), like so:
name
count
quarter
year
orange
22
4
2022
apple
1
4
2022
banana
123
3
2022
pie
93
2
2022
apple
12
2
2022
orange
0
1
2022
I am using Postgres 6.10.
If the next year were reached, it would still need to work with the quarter at the top being 1 and the year 2023.
select name
,count
,quarter
,year
from
(
select *
,dense_rank() over(order by year desc, quarter desc) as dns_rnk
from t
) t
where dns_rnk <= 4
name
count
quarter
year
orange
22
4
2022
apple
1
4
2022
banana
123
3
2022
pie
93
2
2022
apple
12
2
2022
orange
0
1
2022
Fiddle
Related
I would like to group Highest values in month column group by year and Sum the value column
value
Year
Month
4
2019
10
1
2019
11
5
2019
11
1
2019
11
1
2019
12
8
2019
12
1
2019
12
1
2020
1
10
2020
1
3
2021
1
2
2021
2
11
2021
2
1
2021
2
3
2021
2
2
2021
3
In above table I would like to extract highest value of month group by year
in year 2019 highest month is 12 so there are 3 rows and sum of value column will be 10
The output should be
value
Year
Month
10
2019
12
11
2020
1
2
2021
3
supposing that the table is called "example_table" you can use the following query:
select sum(example_table.value), example_table.year, example_table.month
from example_table
join (
select year, max(month) "month"
from example_table
group by year
) sub on example_table.year = sub.year and example_table.month = sub.month
group by example_table.year, example_table.month
order by example_table.year
I have a data frame of sales with three columns: the code of the customer, the month the customer bought that item, and the year.
A customer can buy something in september and then in december make another purchase, so appear two times. But I'm interested in knowing the absolutely new customoers by month and year.
So I have thought in make an iteration and some checks and use the %in% function and build a boolean vector that tells me if a customer is new or not and then count by month and year with SQL using this new vector.
But I'm wondering if there's a specific function or a better way to do that.
This is an example of the data I would like to have:
date cust month new_customer
1 14975 25 1 TRUE
2 14976 30 1 TRUE
3 14977 22 1 TRUE
4 14978 4 1 TRUE
5 14979 25 1 FALSE
6 14980 11 1 TRUE
7 14981 17 1 TRUE
8 14982 17 1 FALSE
9 14983 18 1 TRUE
10 14984 7 1 TRUE
11 14985 24 1 TRUE
12 14986 22 1 FALSE
So put it more simple: the data frame is sorted by date, and I'm interested in a vector (new_customer) that tells me if the customer purchased something for the first time or not. For example customer 25 bought something the first day, and then four days later bought something again, so is not a new customer. The same can be seen with customer 17 and 22.
I create dummy data my self with id, month of numeric format, and year
dat <-data.frame(
id = c(1,2,3,4,5,6,7,8,1,3,4,5,1,2,2),
month = c(1,6,7,8,2,3,4,8,11,1,10,9,1,12,2),
year = c(2019,2019,2019,2019,2019,2020,2020,2020,2020,2020,2021,2021,2021,2021,2021)
)
id month year
1 1 1 2019
2 2 6 2019
3 3 7 2019
4 4 8 2019
5 5 2 2019
6 6 3 2020
7 7 4 2020
8 8 8 2020
9 1 11 2020
10 3 1 2020
11 4 10 2021
12 5 9 2021
13 1 1 2021
14 2 12 2021
15 2 2 2021
Then, group by id and arrange by year and month (order is meaningful). Then use filter and row_number().
dat %>%
group_by(id) %>%
arrange(year, month) %>%
filter(row_number() == 1)
id month year
<dbl> <dbl> <dbl>
1 1 1 2019
2 5 2 2019
3 2 6 2019
4 3 7 2019
5 4 8 2019
6 6 3 2020
7 7 4 2020
8 8 8 2020
Sample Code
You can change in your code according to this logic:-
Create Table:-
CREATE TABLE PURCHASE(Posting_Date DATE,Customer_Id INT,Customer_Name VARCHAR(15));
Insert Data Into Table
Posting_Date Customer_Id Customer_Name
2018-01-01 C_01 Jack
2018-02-01 C_01 Jack
2018-03-01 C_01 Jack
2018-04-01 C_02 James
2019-04-01 C_01 Jack
2019-05-01 C_01 Jack
2019-05-01 C_03 Gill
2020-01-01 C_02 James
2020-01-01 C_04 Jones
Code
WITH Date_CTE (PostingDate,CustomerID,FirstYear)
AS
(
SELECT MIN(Posting_Date) as [Date],
Customer_Id,
YEAR(MIN(Posting_Date)) as [F_Purchase_Year]
FROM PURCHASE
GROUP BY Customer_Id
)
SELECT T.[ActualYear],(CASE WHEN T.[Customer Status] = 'new' THEN COUNT(T.[Customer Status]) END) AS [New Customer]
FROM (
SELECT DISTINCT YEAR(T2.Posting_Date) AS [ActualYear],
T2.Customer_Id,
(CASE WHEN T1.FirstYear = YEAR(T2.Posting_Date) THEN 'new' ELSE 'old' END) AS [Customer Status]
FROM Date_CTE AS T1
left outer join PURCHASE AS T2 ON T1.CustomerID = T2.Customer_Id
) AS T
GROUP BY T.[ActualYear],T.[Customer Status]
Final Result
ActualYear New Customer
2018 2
2019 1
2020 1
2019 NULL
2020 NULL
I need to determine the counts breakdown to per month (and year) of customers [alias'ed as Patient_ID] which made their first visit to a store. The date times of store visits are stored in the [MDT Review Date] column of the table.
Customers can come to the store multiple times throughout the year and increase the total count-> but what I require is ONLY the first time a customer visited.
E.g. Tom Bombadil visited the store once in January 2019, so count increased to 1, then again 4 times in March, so count should be 1 for the month of March and 0 for febraury and 1 for January, then again 4 times in October, then again 2 times in December.
I require that Tom Bombadil should be counted one and only once for a particular month, his first occurrence which was per month
The output should be like :
rn1 YEAR Month_Number Month Total_Count
1 2010 6 June 2
1 2010 7 July 1
1 2010 8 August 5
1 2010 10 October 5
1 2010 11 November 3
1 2011 1 January 4
1 2011 2 February 6
1 2011 4 April 7
1 2011 5 May 4
1 2011 6 June 10
1 2011 7 July 10
1 2011 8 August 14
1 2011 9 September 4
1 2011 10 October 8
1 2011 11 November 11
1 2011 12 December 11
1 2012 1 January 8
1 2012 2 February 21
Please refer to my query. What I have attempts to use the windowing function COUNT to count the store visits per month. Then the ROW_NUMBER function attempts to assign a unique number to each visit. What am I doing wrong?
select
*
from
(select distinct
row_number() over (partition by p.Patient_ID, p.PAT_Forename1, p.PAT_Surname
order by PAT_Forename1, p.Patient_ID, PAT_Surname) AS rn1,
datepart(year, [DATE_COLUMN]) as YEAR,
datepart(month, [DATE_COLUMN]) as Month_Number,
datename(month,[DATE_COLUMN]) as Month,
count(p.Patient_ID) over (partition by datepart(year,[DATE_COLUMN]),
datename(month, [DATE_COLUMN])) as Total_Count
from
Tablename m
inner join
TableName p on m.PK_ID = p.PK_ID
) as temp
where
rn1 = 1
I have a table with the following structure:
Employee Project Task Accomplishment Score Year
John A 1 5 60 2016
John A 1 6 40 2018
John A 2 3 30 2016
Simon B 2 0 30 2017
Simon B 2 4 30 2019
David C 1 3 20 2015
David C 1 2 40 2016
David C 3 0 25 2017
David C 3 5 35 2017
I want to create a view with Oracle SQLout of the above table which looks like as follows:
Employee Project Task Accomplishment Score Year UpdateScore Comment
John A 1 5 60 2016 60
John A 1 6 40 2018 100 (=60+40)
John A 2 3 30 2016 30
Simon B 2 0 30 2017 30
Simon B 2 4 40 2019 40 (no update because Accomplishement was 0)
David C 1 3 20 2015 20
David C 1 2 40 2016 60 (=20+40)
David C 3 0 25 2017 25
David C 3 5 35 2017 35 (no update because Accomplishement was 0)
The Grouping is: Employee-Project-Task.
The Rule of the UpdateScore column:
If for a specific Employee-Project-Task group Accomplishment column value is greater than 0 for the previous year, add the previous year's score to the latest year for the same Employee-Project-Task group.
For example: John-A-1 is a group which is different from John-A-2. So as we can see for John-A-1 the Accomplishment is 5 (which is greater than 0) in 2016, so we add the Score from 2016 with the score of 2018 for the John-A-1 and the updated score becomes 100.
For Simon-B-2, the accomplishment was 0, so there will be no update for 2019 for Simon-B-2.
Note: I don't need the Comment field, it is there just for more clarification.
Use analytic functions to determine if there was a score for the previous year, and if so, add it to the UpdatedScore.
select Employee, Project, Task, Accomplishment, Score, Year,
case when lag(Year) over (partition by Employee, Project order by Year) = Year - 1
then lag(Score) over (partition by Employee, Project order by Year)
else 0
end + Score as UpdatedScore
from EmployeeScore;
This is a bit strange -- you are counting the accomplishment of 0 in one year but not the next. Okay.
Use analytic functions:
select t.*,
(case when lag(accomplishment) over (partition by Employee, Project, Task order by year) > 0
then lag(score) over (partition by Employee, Project, Task order by year)
else 0
end) + score as update_score
from t;
from t
My sql table is
Week Year Applications
1 2017 0
2 2017 10
3 2017 20
4 2017 50
5 2017 0
1 2018 10
2 2018 0
3 2018 40
4 2018 50
5 2018 10
And I want SQL query which give below output
Week Year Applications
1 2017 0
2 2017 10
3 2017 30
4 2017 80
5 2017 80
1 2018 10
2 2018 10
3 2018 50
4 2018 100
5 2018 110
Can anyone help me to write below query?
You could use SUM() OVER to get cumulative sum:
SELECT *, SUM(Applications) OVER(PARTITION BY Year ORDER BY Week)
FROM tab
It looks like you want a cumulative sum:
select week, year,
sum(applications) over (partition by year order by week) as cumulative_applications
from t;