I have a SQLite table called posts. An example is shown below. I would like to calculate the monthly income and expenses.
accId date text amount balance
---------- ---------- ------------------------ ---------- ----------
1 2008-03-25 Ex1 -64.9 3747.56
1 2008-03-25 Shop2 -91.85 3655.71
1 2008-03-26 Benny's -100.0 3555.71
For the income I have this query:
SELECT SUBSTR(date, 0,7) "month", total(amount) "income" FROM posts
WHERE amount > 0 GROUP BY month ORDER BY date;
It works fine:
month income
---------- ----------
2007-05 4877.0
2007-06 8750.5
2007-07 8471.0
2007-08 5503.0
Now I need the expenses and I could of cause just repeat the first statement with the condition amount < 0, but I am wondering if there is an elegant way to get both income and expenses in one query?
Try something like this
select substr(date, 0,7) "Month",
total(case when a > 0 then a else 0 end) "Income",
total(case when a < 0 then a else 0 end) "Expenses"
from posts
group by month
Look into the UNION statement (bottom of the link). This will let you combine the results of two queries, generally in the form:
<SELECT_STATEMENT_1> UNION <SELECT_STATEMENT_2>
Not sure if SQL Lite supports CASE statements, but if it does you could do something like this.
SELECT SUBSTR(date, 0,7) "month"
, total(CASE WHEN Amount > 0 THEN Amount ELSE 0 END) "income"
, -1 * total(CASE WHEN Amount < 0 THEN Amount ELSE 0 END) "expenses"
FROM posts
GROUP BY month
ORDER BY date;
Related
I searched the forum but couldn't find a problem like the one I have. I have a table called Journal Table and it has the following data:
A transaction is considered to be sales if the Quantity>0 otherwise it's a loan transaction. Now my question is how can I count the total number of transactions as Sales Per month.
Like:
Month | TotalSales
1 5
2 3
3 7
I tried the following but got the wrong output:
Select DISTINCT Month(date) AS 'Month',
(Select COUNT(TransactionID) from journalTable where Quantity>0)
AS 'Total Sales' from journalTable;
Here is a picture of the output:
The output is wrong as it counts the total of all months and shows it for each month. It should count each month's total and show it.
Just group by and conditionally sum.
select Month(date) as 'Month'
, sum(case when Quantity > 0 then 1 else 0 end) as 'Total Sales'
-- You can even add a count of loans at the same time.
, sum(case when Quantity <= 0 then 1 else 0 end) as 'Total Loans'
from journalTable
group by Month(date);
Something like this
SELECT MONTH(DATE) AS MONTH, COUNT(QUANTITY)CNTT
FROM TRANSACTIONS
WHERE QUANTITY > 0
GROUP BY MONTH(DATE)
I have list of line items from invoices with a field that indicates if a line was delivered or picked up. I need to find a percentage of delivered items from the total number of lines.
SALES_NBR | Total | Deliveryrate
1 = Delivered 0 = picked up from FULFILLMENT.
SELECT SALES_NBR,
COUNT (ITEMS) as Total,
SUM (case when FULFILLMENT = '1' then 1 else 0 end) as delivered,
(SELECT delivered/total) as Deliveryrate
FROM Invoice_table
WHERE STORE IN '0123'
And SALE_DATE >='2020-02-01'
And SALE_DATE <='2020-02-07'
Group By SALES_NBR, Deliveryrate;
My query executes but never finishes for some reason. Is there any easier way to do this? Fulfillment field does not contain any NULL values.
Any help would be appreciated.
I need to find a percentage of delivered items from the total number of lines.
The simplest method is to use avg():
select SALES_NBR,
avg(fulfillment) as delivered_ratio
from Invoice_table
where STORE = '0123' and
SALE_DATE >='2020-02-01' and
SALE_DATE <='2020-02-07'
group by SALES_NBR;
I'm not sure if the group by sales_nbr is needed.
If you want to get a "nice" query, you can use subqueries like this:
select
qry.*,
qry.delivered/qry.total as Deliveryrate
from (
select
SALES_NBR,
count(ITEMS) as Total,
sum(case when FULFILLMENT = '1' then 1 else 0 end) as delivered
from Invoice_table
where STORE IN '0123'
and SALE_DATE >='2020-02-01'
and SALE_DATE <='2020-02-07'
group by SALES_NBR
) qry;
But I think this one, even being ugglier, could perform faster:
select
SALES_NBR,
count(ITEMS) as Total,
sum(case when FULFILLMENT = '1' then 1 else 0 end) as delivered,
sum(case when FULFILLMENT = '1' then 1 else 0 end)/count(ITEMS) as Deliveryrate
from Invoice_table
where STORE IN '0123'
and SALE_DATE >='2020-02-01'
and SALE_DATE <='2020-02-07'
group by SALES_NBR
Full disclosure, I am learning and I have searched all over the internet and I just can't figure out my question.
I am working on an online class and was given the following example:
select
DATENAME(MONTH, DATEADD(MONTH, MONTH(OrderDate), -1)) AS 'Month',
SUM(CASE WHEN YEAR(OrderDate) = 2005 THEN 1 ELSE 0 END) AS Orders,
SUM(CASE YEAR(OrderDate) WHEN 2005 THEN Totaldue ELSE 0 END) AS 'Total Value'
from
sales.salesorderheader
group by Month(orderdate)
order by Month(orderdate) ASC
That returns the following results:
I understood that (I thought) so I began messing around with the code to further understand Case statements. Looking at the code I thought that the Orders field was essentially finding all the orders in a month, assigning a 1 to each one, and then adding them all up. Because each one was assigned a 1 I figured that I could change the SUM to COUNT and I would get the same results.
However, this code:
select
DATENAME(MONTH, DATEADD(MONTH, MONTH(OrderDate), -1)) AS 'Month',
COUNT(CASE WHEN YEAR(OrderDate) = 2005 THEN 1 ELSE 0 END) AS Orders,
SUM(CASE YEAR(OrderDate) WHEN 2005 THEN Totaldue ELSE 0 END) AS 'Total Value'
from
sales.salesorderheader
group by Month(orderdate)
order by Month(orderdate) ASC
Returns these results:
To try and break this down I created a query that would just look for the orders in January 2005 and count them.
SELECT COUNT(*)
FROM Sales.SalesOrderHeader
WHERE OrderDate >= '1/1/2005' AND OrderDate < '1/1/2005'
This returned 0. The same as the SUM query. I get that COUNT counts rows and SUM sums numbers in a column, but I just don't understand the results I'm getting. Could someone please explain why the count query is returning 2483 for January and not 0?
For COUNT 1 and 0 are the same. What you really need is NULL:
COUNT(ALL expression) evaluates expression for each row in a group and returns the number of nonnull values.
select
DATENAME(MONTH, DATEADD(MONTH, MONTH(OrderDate), -1)) AS 'Month',
COUNT(CASE WHEN YEAR(OrderDate) = 2005 THEN 1 ELSE NULL END) AS Orders,
SUM(CASE YEAR(OrderDate) WHEN 2005 THEN Totaldue ELSE 0 END) AS 'Total Value'
from sales.salesorderheader
group by Month(orderdate)
order by Month(orderdate) ASC;
Or even shorter(default ELSE is NULL so we could omit that part)
COUNT(CASE WHEN YEAR(OrderDate) = 2005 THEN 1 END) AS Orders,
Example:
SUM COUNT COUNT
2005 1 1 1
2006 0 0 NULL
2007 0 0 NULL
2005 1 1 1
===============================================
2 4 2
When you use count(*) you count ALL the rows. If you want to count how many orders you have, you have to use a column: eg: count(OrderDate). Try it
count example:
assume that your column has 3 value and column name is the order
2 ---------- 5 ---------- 4----- Null
now if you run
count (order)
it will return = 3 how many entries you have in the column without null
sum example:
2 ---------- 5 ---------- 4
now if you run
sum (order)
it will return = 2+5+4=11 its add all the entries
I'm calculating historical amount from a table in years(ex. 2015-2016, 2014-2015, etc.) I would like to seek expertise if its more efficient to do it in one batch or repeat the query multiple times filtered by the date required.
Thanks in advance!
OPTION 1:
select
id,
sum(case when year(getdate()) - year(txndate) between 5 and 6 then amt else 0 end) as amt_6_5,
...
sum(case when year(getdate()) - year(txndate) between 0 and 1 then amt else 0 end) as amt_1_0,
from
mytable
group by
id
OPTION 2:
select
id, sum(amt) as amt_6_5
from
mytable
group by
id
where
year(getdate()) - year(txndate) between 5 and 6
...
select
id, sum(amt) as amt_1_0
from
mytable
group by
id
where
year(getdate()) - year(txndate) between 0 and 1
1.
Unless you have resources issues I would go with the CASE version.
Although it has no impact on the results, filtering on the requested period in the WHERE clause might have a significant performance advantage.
2. Your period definition creates overlapping.
select id
,sum(case when year(getdate()) - year(txndate) = 6 then amt else 0 end) as amt_6
-- ...
,sum(case when year(getdate()) - year(txndate) = 0 then amt else 0 end) as amt_0
where txndate >= dateadd(year, datediff(year,0, getDate())-6, 0)
from mytable
group by id
This may be help you,
WITH CTE
AS
(
SELECT id,
(CASE WHEN year(getdate()) - year(txndate) BETWEEN 5 AND 6 THEN 'year_5-6'
WHEN year(getdate()) - year(txndate) BETWEEN 4 AND 5 THEN 'year_4-5'
...
END) AS my_year,
amt
FROM mytable
)
SELECT id,my_year,sum(amt)
FROM CTE
GROUP BY id,my_year
Here, inside the CTE, just assigned a proper year_tag for each records (based on your conditions), after that select a summary for the CTE grouped by that year_tag.
(Also posted here.)
So I have two tables, one is invalid table and the other is valid table.
valid table:
id
status
date
invalid table:
id
status
date
I have to produce a report with this output:
date on-time late total valid invalid1 invalid2 total rate
--------- ------- ---- ----- ----- -------- -------- ----- ----
9/10/2011 4 10 14 3 3 3 6
date: common fields on the 2 tables, field to group by, how many records on that day has
on-time: count of all the id on the valid table
late: count of all the records(id) on the invalid table
total: total of on-time and late
valid: count of id on the valid table with the "valid" status
invalid1: count of id on the invalid table with "invalid1" status
invalid2: count of id on the invalid table with "invalid2" status
total: total of valid, invalid1, invalid2
rate: average of totals
It's basically multiple queries with different table. How can I achieve it?
Someting like this?
SELECT
*,
(result.total + result._total) / 2 AS rate
FROM (
SELECT
date,
SUM(CASE WHEN data.valid = 1 THEN 1 ELSE 0 END) AS ontime,
SUM(CASE WHEN data.valid = 0 THEN 1 ELSE 0 END) AS late,
COUNT(*) AS total,
SUM(CASE WHEN data.valid = 1 AND data.status = 'valid' THEN 1 ELSE 0 END) AS valid,
SUM(CASE WHEN data.valid = 0 AND data.status = 'invalid1' THEN 1 ELSE 0 END) AS invalid1,
SUM(CASE WHEN data.valid = 0 AND data.status = 'invalid2' THEN 1 ELSE 0 END) AS invalid2,
SUM(CASE WHEN data.status IN ('valid', 'invalid', 'invalid2') THEN 1 ELSE 0 END) AS _total
FROM (
SELECT
date,
status,
valid = 1
FROM
Valid
UNION ALL
SELECT
date,
status,
valid = 0
FROM
InValid ) AS data
GROUP BY
date) AS result
SELECT date, ontime, late, ontime+late total, valid, invalid1, invalid2, valid+invalid1+invalid2 total
FROM
(SELECT date,
COUNT(*) late,
COUNT(IIF(status = 'invalid1', 1, NULL)) invalid1,
COUNT(IIF(status = 'invalid2', 1, NULL)) invalid2,
FROM invalid
GROUP BY date
) JOIN (
SELECT date,
COUNT(*) ontime,
COUNT(IIF(status = 'valud', 1, NULL)) valid,
FROM valid
GROUP BY date
) USING (date)
First of all, it seems that you are holding exactly the same information in 2 tables - I would recommend merging those tables together and add an additional boolean column called valid to hold the info related to validity of the record.
The query on your existent DB structure might look something like this:
SELECT unioned.* FROM (
( SELECT v.date AS date, v.status AS status, v.id AS id, COUNT(id) AS valid, 0 AS invalid1, 0 AS invalid2 FROM valid v GROUP BY v.date)
UNION
( SELECT i1.date AS date, i1.status AS status, i1.id AS id, 0 AS valid, COUNT(i1.id) AS invalid1, 0 AS invalid2 FROM invalid1 i1 GROUP BY i1.date)
UNION
( SELECT i2.date AS date, i2.status AS status, i2.id AS id, 0 AS valid, 0 AS invalid1, COUNT(i.id) AS invalid2 FROM invalid1 i1 GROUP BY i1.date)
) AS unioned GROUP BY unioned.date