I have programmed a PaypalRequest Paypal where:
BILLINGPERIOD = Day
BILLINGFREQUENCY = 1
AMT = 10
TOTALBILLINGCYCLES = 3
Customer buys a reservation at a hotel, valued at USD 10.00, for 3 days
He will pay 10 USD each day until he completes 3 days.
How can I make it pay 3x 10 USD the same day?
Related
I got the following sample data:
Product Group Product Monthly Start Date Sales Qty
Mobile Phone A Mobile Phone A-1 1/1/2021 100
Mobile Phone A Mobile Phone A-1 2/1/2021 120
Mobile Phone B Mobile Phone B-1 1/1/2021 90
Mobile Phone B Mobile Phone B-1 2/1/2021 78
What I want is to calculate the Monthly product growth rate (below).
Product Group Product Month Start Date Growth Rate
Mobile Phone A Mobile Phone A-1 1/1/2021 null
Mobile Phone A Mobile Phone A-1 2/1/2021 20%
Mobile Phone B Mobile Phone B-1 1/1/2021 null
Mobile Phone B Mobile Phone B-1 2/1/2021 -13%
I guess I need to use groupby and sort order by the Month Start Date and calculate the rate.
Does anyone know the best way of calculating it?
Thanks.
I would do it this way (assuming you are viewing the result with a monthly granularity):
Total Sales Qty = SUM( ExampleTable[Sales Qty] )
MTD Sales Qty =
TOTALMTD( [Total Sales Qty], Dates[Date] )
MTD Sales Qty LM =
CALCULATE( [MTD Sales Qty], DATEADD(Dates[Date], -1, MONTH ) )
MoM Sales Qty Change =
DIVIDE([MTD Sales Qty] - [MTD Sales Qty LM], [MTD Sales Qty LM], BLANK() )
You would calculate month-over-month growth using a sequence of four measures:
sum of the column
amount for the prior month
change month-over-month
change month-over-month %
These DAX patterns can can be used to get you started. Make sure you add the necessary columns to your date table, then modify the measures below with your date table, fact table column to be quantified and measures you create.
DAX Patterns - Month Related Calculations
Sum of the Fact Table Column
Sales Amount:= sum ( SalesTable[Sales Qty] )
Amount for Prior Month
Sales PM :=
VAR CurrentYearMonthNumber = SELECTEDVALUE ( 'Date'[Year Month Number] )
VAR PreviousYearMonthNumber = CurrentYearMonthNumber - 1
VAR Result =
CALCULATE (
[Sales Amount],
REMOVEFILTERS ( 'Date' ),
'Date'[Year Month Number] = PreviousYearMonthNumber
)
RETURN
Result
Change Month-Over-Month
Sales MOM :=
VAR ValueCurrentPeriod = [Sales Amount]
VAR ValuePreviousPeriod = [Sales PM]
VAR Result =
IF (
NOT ISBLANK ( ValueCurrentPeriod ) && NOT ISBLANK ( ValuePreviousPeriod ),
ValueCurrentPeriod - ValuePreviousPeriod
)
RETURN
Result
Change Month-Over-Month %
Sales MOM % :=
DIVIDE (
[Sales MOM],
[Sales PM]
)
CREATE TABLE beauty.customer_payments
(
customer_id integer,
date date,
amount numeric(10,2),
CONSTRAINT customer_payments_customer_id_fkey FOREIGN KEY (customer_id)
REFERENCES beauty.customers (customer_id) MATCH SIMPLE
ON UPDATE NO ACTION
ON DELETE NO ACTION
)
CREATE TABLE beauty.sales
(
product_id integer,
customer_id integer,
sell_date date NOT NULL,
qty integer NOT NULL,
sell_price numeric(10,2) NOT NULL,
expiry_date date NOT NULL,
CONSTRAINT sales_customer_id_fkey FOREIGN KEY (customer_id)
REFERENCES beauty.customers (customer_id) MATCH SIMPLE
ON UPDATE NO ACTION
ON DELETE NO ACTION,
CONSTRAINT sales_product_id_fkey FOREIGN KEY (product_id)
REFERENCES beauty.products (product_id) MATCH SIMPLE
ON UPDATE NO ACTION
ON DELETE NO ACTION
)
Balance of payments beauty.customer_payments for customer_id=6 is 0
SELECT * FROM beauty.customer_payments
WHERE customer_id=6;
customer_id
date
amount
6
2020-11-14
75.00
6
2020-11-14
-75.00
SELECT * FROM beauty.sales
WHERE customer_id=6;
product_id
customer_id
sell_date
qty
sell_price
expiry_date
76
6
2020-11-14
1
75.00
2022-03-03
83
6
2020-11-14
1
10.00
2022-06-23
85
6
2020-11-14
1
10.00
2022-06-23
44
6
2020-11-14
1
12.00
2022-06-23
41
6
2020-11-14
1
15.00
2022-03-26
96
6
2020-11-14
1
75.00
2022-03-15
28
6
2020-11-14
1
4.00
2022-01-22
33
6
2020-11-14
1
4.00
2023-01-23
37
6
2020-11-14
1
4.00
2023-01-23
40
6
2020-11-14
1
4.00
2023-08-13
(10 rows)
SELECT customer_id, SUM(qty * sell_price) AS purchased
FROM beauty.sales
WHERE customer_id=6
GROUP BY customer_id;
customer_id
purchased
6
213.00
SELECT s.customer_id,
SUM(qty * sell_price) AS purchased,
SUM(cp.amount) AS paid,
SUM(qty * sell_price - cp.amount) AS balance
FROM beauty.sales s
INNER JOIN beauty.customer_payments cp
ON cp.customer_id = s.customer_id
WHERE s.customer_id=6
GROUP BY s.customer_id;
customer_id
purchased
paid
balance
6
1065.00
0.00
1065.00
Please advise WHY after adding JOIN (INNER, LEFT, RIGHT) calculation goes wrong and how to solve this multi-calculation issue?
As I see similar question all of them based on not cross-tables calculations like SUM(qty * sell_price - cp.amount)
Delete payments
`
DELETE FROM beauty.customer_payments
WHERE customer_id=6;`
Add new ZERO payment
INSERT INTO beauty.customer_payments(
customer_id, date, amount)
VALUES (6, '2020-11-17', 0);
customer_id
purchased
paid
balance
6
213.00
0.00
213.00
Add payment 10
INSERT INTO beauty.customer_payments(
customer_id, date, amount)
VALUES (6, '2020-11-17', 10);
SELECT * FROM beauty.customer_payments WHERE customer_id=6;
customer_id
date
amount
6
2020-11-17
0.00
6
2020-11-17
10.00
SELECT s.customer_id,
.......
INNER JOIN beauty.customer_payments cp
.......
customer_id
purchased
paid
balance
6
426.00
100.00
326.00
Correct payment with negative amount
INSERT INTO beauty.customer_payments(
customer_id, date, amount)
VALUES (6, '2020-11-17', -10);
SELECT * FROM beauty.customer_payments WHERE customer_id=6;
customer_id
date
amount
6
2020-11-17
0.00
6
2020-11-17
10.00
6
2020-11-17
-10.00
SELECT s.customer_id,
.......
INNER JOIN beauty.customer_payments cp
.......
customer_id
purchased
paid
balance
6
639.00
0.00
639.00
What is this `INNER JOIN' calculate?
In general, you probably wouldn't want to match each payment to each sale (unless there's an additional identifier matching specific payments to specific sales, not just matching each to a customer).
If a customer has 2 sales for $10 and $15, and two payments for $9 and $14, your join is going to match each payment to each sale for that customer, creating something like
Sale
Payment
$10
$9
$10
$14
$15
$9
$15
$14
So the sum of the sales after the join will be $50, not $25 (as you might be expecting). I think the above answers your question about why the join doesn't do what you expect.
The exact query you want might be a little different (do you want all customers even if they have no sales? is it possible for customers to have payments if they don't have a sale?), but in general I'd expect something like the following to work. There are multiple ways of doing this, but I think the following is easy to understand since it aggregates the data into one payment row per customer and one sales row per customer before joining them.
SELECT
s.customer_id,
s.purchased,
cp.amount as paid,
s.purchased - cp.amount as balance
FROM
(SELECT s.customer_id,
SUM(s.qty * s.sell_price) AS purchased
FROM beauty.sales s
GROUP BY s.customer_id) s
LEFT OUTER JOIN
(SELECT cp.customer_id,
SUM(cp.amount) AS amount
FROM beauty.customer_payments cp
GROUP BY cp.customer_id) cp
ON s.customer_id = cp.customer_id
WHERE s.customer_id = 6
I have the following trade table:
time ticker side price qty
--------------------------
2018.01.01T13:00:20 AAPL BUY 10.0 100
2018.01.01T13:01:30 AAPL SELL 12.0 300
2018.01.01T13:01:45 AAPL BUY 11.0 500
2018.01.01T13:02:13 AAPL BUY 10.5 100
2018.01.01T13:05:00 AAPL SELL 13.0 200
I need a rolling window function with a lookback of 1 minute to seperate the buy/sells of a stock price
time ticker BUYs SELLs TOTAL
--------------------------------
2018.01.01T13:00:20 AAPL 1 0 1
2018.01.01T13:01:30 AAPL 0 1 1
2018.01.01T13:01:45 AAPL 1 1 2
2018.01.01T13:02:13 AAPL 1 1 2
2018.01.01T13:05:00 AAPL 0 1 1
I have decided on using the "wj" function, because the rolling function suit my purpose. However I can't get it to work:
w: -00:01 00:00 +:/ select time from table
wj[w;'ticker'time;table;(table;(count;ticker);(count;ticker))]
So at least I want the count every buy/sell first then group them later. But I cannot even get the initial query to run without getting a type error.
Can someone point me in the right direction?
Additional Question
I know would have to perform a rolling sum/count over several accounts which is not known until runtime.
time ticker side price qty account
----------------------------------
2018.01.01T13:00:20 AAPL BUY 10.0 100 ACCT123
2018.01.01T13:01:30 AAPL SELL 12.0 300 ACCT456
2018.01.01T13:01:45 AAPL BUY 11.0 500 ACCT789
2018.01.01T13:02:13 AAPL BUY 10.5 100 ERRORACCT123
2018.01.01T13:05:00 AAPL SELL 13.0 200 TESTACCT123
I know I can pivot the table to:
time ticker side price qty ACCT123 ACCT456 ACC789 ERRORACCT123 TESTACCT23
---------------------------------
but can I using the rolling function to sum the sizes in a 1 minute lookback period?
The window w is required to be a pair of lists:
w: -00:01 00:00 +\: exec time from t
You'll also need to use wj1 as you only want to consider rows on or after entry to the window.
http://code.kx.com/q/ref/joins/#wj-wj1-window-join
q)table,'exec side from wj1[w;`ticker`time;table;(table;({`BUY`SELL!count each (group x)`BUY`SELL};`side))]
The monadic lambda:
{`BUY`SELL!count each (group x)`BUY`SELL}
Uses group to return the indices of BUY and SELL values and also ensures that BUY and SELL are present in all keys.
exec creates a table:
q)exec side from wj1[w;`ticker`time;table;(table;({{`BUY`SELL!count each x`BUY`SELL}group x};`side))]
BUY SELL
--------
1 0
0 1
1 1
2 1
0 1
And then we use join each to get the final result:
q)update TOTAL:BUY+SELL from table,'exec side from wj1[w;`ticker`time;table;(table;({`BUY`SELL!count each (group x)`BUY`SELL};`side))]
time ticker side price qty BUY SELL TOTAL
------------------------------------------------------------------
2018.01.01D13:00:20.000000000 AAPL BUY 10 100 1 0 1
2018.01.01D13:01:30.000000000 AAPL SELL 12 300 0 1 1
2018.01.01D13:01:45.000000000 AAPL BUY 11 500 1 1 2
2018.01.01D13:02:13.000000000 AAPL BUY 10.5 100 2 1 3
2018.01.01D13:05:00.000000000 AAPL SELL 13 200 0 1 1
For summing quantities depending on side it is easier to the following:
First update two new columns using vector conditional and then sum these using wj1.
http://code.kx.com/q/ref/lists/#vector-conditional
q)wj1[w;`ticker`time;table;(update BUYQUANTITY:?[`BUY=side;qty;0],SELLQUANTITY:?[`SELL=side;qty;0]from table;(sum;`BUYQUANTITY);(sum;`SELLQUANTITY))]
time ticker side price qty BUYQUANTITY SELLQUANTITY
----------------------------------------------------------------------------
2018.01.01D13:00:20.000000000 AAPL BUY 10 100 100 0
2018.01.01D13:01:30.000000000 AAPL SELL 12 300 0 300
2018.01.01D13:01:45.000000000 AAPL BUY 11 500 500 300
2018.01.01D13:02:13.000000000 AAPL BUY 10.5 100 600 300
2018.01.01D13:05:00.000000000 AAPL SELL 13 200 0 200
w: -00:01 00:00 +\: exec time from table
Using an exec will allow you to create a pair of times or timestamps for the time interval to join on. You must also use \: to perform the each left operation.
wj[w;`sym`time;table;(table;(count;`sym);(count;`sym))]
w defines the time interval - a pair of times or timestamps;
The table names in the window join must also be passed in as a symbol using `.
I have a little question about recurring payments in paypal.
Example: I start a recurring payment, 20$ for each month during 1 year.
Does paypal send an IPN for every month of this recurring payment?
Thanks.
Yes. Here's a sample of what an IPN for a recurring payment looks like.
period_type = Regular
outstanding_balance = 0.00
next_payment_date = 02:00:00 Dec 19, 2012 PST
protection_eligibility = Ineligible
payment_cycle = Monthly
tax = 0.00
payer_id = E7BTGVXBFSUAU
payment_date = 05:38:59 Nov 19, 2012 PST
payment_status = Completed
product_name = ElderHelpers.org
charset = windows-1252
recurring_payment_id = I-PFSGNJYBXBH5
first_name = Drew
mc_fee = 0.65
notify_version = 3.7
amount_per_cycle = 12.00
payer_status = verified
currency_code = USD
business = sandbo_1215254764_biz#angelleye.com
verify_sign = AUivUYns031-2-dNgZdEkr51EzGcAF5d4-6xZ2neOdkff7tDdERk1R9k
payer_email = sandbo_1204199080_biz#angelleye.com
initial_payment_amount = 0.00
profile_status = Active
amount = 12.00
txn_id = 3GN39710BA809992V
payment_type = instant
payer_business_name = Drew Angell's Test Store
last_name = Angell
receiver_email = sandbo_1215254764_biz#angelleye.com
payment_fee = 0.65
receiver_id = ATSCG2QMC9KAU
txn_type = recurring_payment
mc_currency = USD
residence_country = US
test_ipn = 1
transaction_subject = ElderHelpers.org
payment_gross = 12.00
shipping = 0.00
product_type = 1
time_created = 21:19:38 Dec 19, 2011 PST
ipn_track_id = b6f7576ff1e68
I have a list of purchases by date. EG:
ItemCode, Purchase Date, Purchase Qty
XXX, 01 Jan 2012, 10
XXX, 10 Jan 2012, 5
For the item I have a corresponding Sales transactions:
Item, Sales Date, Sales Qty
XXX, 02 Jan 2012, -5
XXX, 09 Jan 2012, -3
XXX, 11 JAN 2012, -3
I am looking to get a SQL query (Without a cursor), to get the balance on each purchase order quantity. I.e Run each purchase (First in first out) to 0. (For the purposes of aging inventory )
How can you join the Purchases to the Sales to get this balance remaining each purchased Inventory Lot? Is this possible without a cursor?
Yes.
You union the two tables together, and run a running total on the resulting set.
;with cte as
(
select itemcode, purchasedate as tdate, purchaseqty as qty from purchases
union
select itemcode, salesdate, salesqty from sales
)
select
t1.*,
SUM(t2.qty)
from cte t1
left join cte t2
on t1.tdate>=t2.tdate
and t1.item = t2.item
group by t1.item, t1.pdate, t1.qty
To get the stock remaining at any particular time the same principal applies.
select p1.*,
case when (select SUM(abs(qty)) from sales) > SUM(p2.qty) then 0
else SUM(p2.qty) - (select SUM(abs(qty)) from sales) end as stockremaining
from purchases p1
left join purchases p2 on p1.item = p2.item
and p2.purchasedate <= p1.purchasedate
group by p1.purchasedate, p1.item, p1.qty
gives
1 2012-01-01 10 0
1 2012-01-10 5 4