Please see my data below;
data finance;
input id loan1 loan2 loan3 assets home$ type;
datalines;
1 93000 98000 45666 new 1
1 98000 45678 98765 67 old 2
1 55000 56764 435371 54 new 1
2 7000 6000 7547 57 new 1
4 67333 87444 98666 34 old 1
4 98000 68777 986465 23 new 1
5 4555 334 652 12 new 1
5 78999 98999 80000 34 new 1
5 889 989 676 3 new 1
;
data finance1;
set finance;
if loan1<80000 then conc'level1';
if loan2 <80000 and home='new' then borrowcap = 'high';
run;
I would like the following dataset, as you can see although there are multiple rows for each ID initially, if there was a level1 or high in any of those rows, I would like to capture that in the same row.
data finance;
input id conc$ borrowcap$;
datalines;
1 level1 high
2 level1 high
4 level1
5 level1 high
;
Any help is appreciated!
Use retain statement, you can keep value from any row for each ID. Use by statement + if last.var statement, you can keep only one row for each ID.
data finance;
input id loan1 loan2 loan3 assets home$ type;
datalines;
1 93000 98000 45666 . new 1
1 98000 45678 98765 67 old 2
1 55000 56764 435371 54 new 1
2 7000 6000 7547 57 new 1
4 67333 87444 98666 34 old 1
4 98000 68777 986465 23 new 1
5 4555 334 652 12 new 1
5 78999 98999 80000 34 new 1
5 889 989 676 3 new 1
;
data finance1;
set finance;
by id;
retain conc borrowcap;
length conc borrowcap $8.;
if first.id then call missing(conc,borrowcap);
if loan1<80000 then conc='level1';
if loan2<80000 and home='new' then borrowcap = 'high';
if last.id;
run;
I am attempting to return day of the week (i.e. Monday = 1, Tuesday = 2, etc) based on a date column ("Posting_date"). I tried a for loop but got it wrong:
#First date of table was a Sunday (1 March 2019) => so counter starts at 6
posting_df3['Day'] = (posting_df3['Posting_date'] - dt.datetime(2019,3,31)).dt.days.astype('int16')
# Start counter on the right date (31 March 2019 is a Sunday)
count = 7
for x in posting_df3['Day']:
if count != 7:
count = 1
else:
count = count + 1
posting_df3['Day'] = count
Not sure if there are other ways of doing this. Attached is an image of my database structure:
level_0 Posting_date Reservation date Book_window ADR Day
0 9 2019-03-31 2019-04-01 -1 156.00 0
1 25 2019-04-01 2019-04-01 0 152.15 1
2 11 2019-04-01 2019-04-01 0 149.40 1
3 42 2019-04-01 2019-04-01 0 141.33 1
4 45 2019-04-01 2019-04-01 0 159.36 1
... ... ... ... ... ... ...
4278 739 2020-02-21 2019-04-17 310 253.44 327
4279 739 2020-02-22 2019-04-17 310 253.44 328
4280 31 2020-03-11 2019-04-01 345 260.00 346
Final output should be 2019-03-31 Day column should return 7 since it is a Sunday
and 2019-04-01 Day column should return 1 since its Monday etc
You can do it this way
df['weekday']=pd.to_datetime(df['Posting_date']).dt.weekday+1
Input
level_0 Posting_date Reservation_date Book_window ADR Day
0 9 3/31/2019 4/1/2019 -1 156.00 0
1 25 4/1/2019 4/1/2019 0 152.15 1
2 11 4/1/2019 4/1/2019 0 149.40 1
3 42 4/1/2019 4/1/2019 0 141.33 1
4 45 4/1/2019 4/1/2019 0 159.36 1
Output
level_0 Posting_date Reservation_date Book_window ADR Day weekday
0 9 3/31/2019 4/1/2019 -1 156.00 0 7
1 25 4/1/2019 4/1/2019 0 152.15 1 1
2 11 4/1/2019 4/1/2019 0 149.40 1 1
3 42 4/1/2019 4/1/2019 0 141.33 1 1
4 45 4/1/2019 4/1/2019 0 159.36 1 1
Any help is much appreciated. Thanks
I would like to create a couple of variables with my transactional data
I am trying to create variables 'act_bal' and 'penalty' using amount, type and Op_Bal. The rules I have are:
For the first record, the id will have op_bal and it will be
subtracted from the 'amount' for type=C and added if type=D to
calculate act_bal
For the second record onwards it is act_bal + amount for type=C and
act_bal-amount for type=D
I will add the penalty 10 only if the amount is >4 and the type=D.
The id can have only two penalties.
Total Penalty should be subtracted from the act_bal of the last
record which would become op_bal for the next day. (e.g. for id
101, -178-20=-198 will become the op_bal for 4/2/2019)
This is the data I have for two customers IDs 101 and 102 for two different dates (My actual dataset has the data for all the 30 days).
id date amount type Op_Bal
101 4/1/2019 50 C 100
101 4/1/2019 25 D
101 4/1/2019 75 D
101 4/1/2019 3 D
101 4/1/2019 75 D
101 4/1/2019 75 D
101 4/2/2019 100 C
101 4/2/2019 125 D
101 4/2/2019 150 D
102 4/1/2019 50 C 125
102 4/1/2019 125 C
102 4/2/2019 250 D
102 4/2/2019 10 D
The code I wrote is like this
data want;
set have;
by id date;
if first.id or first.date then do;
if first.id then do;
if type='C' then act_bal=Op_Bal - amount;
if type='D' then act_bal=Op_Bal + amount;
end;
else do;
retain act_bal;
if type='C' then act_bal=act_bal + amount;
if type='D' then act_bal=act_bal - amount;
if amount>4 and type='D' then do;
penalty=10;
end;
run;
I couldn't create a counter to control the penalties to 2 and could not subtract the total penalty amount from the amount of the last row. Could someone help me in receiving the desired result? Thanks
id date amount type Op_Bal act_bal penalty
101 4/1/2019 50 C 200 150 0
101 4/1/2019 25 D 125 0
101 4/1/2019 150 D -25 10
101 4/1/2019 75 D -100 10
101 4/1/2019 3 D -103 0
101 4/1/2019 75 D -178 0
101 4/2/2019 100 C -198 -98 0
101 4/2/2019 125 D -223 10
101 4/2/2019 150 D -373 10
102 4/1/2019 50 C 125 175 0
102 4/1/2019 125 C 300 0
102 4/2/2019 250 D 50 0
102 4/2/2019 10 D 40 0
A few tips:
You have the same code for incrementing act_bal in both the if and else blocks, so factor it out. Don't repeat yourself.
You can skip the retain statement if you use a sum statement.
Use a separate variable to keep track of the number of penalties triggered per day, but only apply the first two of them.
So, putting it all together:
data want;
set have;
by id date;
if first.date and not first.id then op_bal = act_bal;
if first.date then do;
act_bal = op_bal;
penalties = 0;
end;
if type='C' then act_bal + amount;
if type='D' then act_bal + (-amount);
if amount > 4 and type='D' then penalties + 1;
if last.date then act_bal + (-min(penalties,2) * 10);
run;
I have problem that I find very hard to solve:
I need to calculate a column R_t in SQL where for each row, the sum of the "previous" calculated values SUM(R_t-1) is required as input. The calculation is done grouped over a ProjectID column. I have no clue how to proceed.
The formula for the calculation I am trying to achieve is R_t = ([Contract value]t - SUM(R{t-1})) / [Remaining Hours]_t * [HoursRegistered]t where "t" denotes time and SUM(R{t-1}) is the sum of R_t from t = 0 to t-1.
Time is always consecutive and always begin in t = 0. But number of time periods may differ across [ProjectID], i.e. one project having t = {0,1,2} and another t = {0,1,2,3,4,5}. The time period will never "jump" from 5 to 7
The expected output (using the data from below is) for ProjectID 101 is
R_0 = (500,000 - 0) / 500 * 65 = 65,000
R_1 = (500,000 - (65,000)) / 435 * 100 = 100,000
R_2 = (500,000 - (65,000 + 100,000)) / 335 * 85 = 85,000
R_3 = (500,000 - (65,000 + 100,000 + 85,000)) / 250 * 69 = 69,000
etc...
This calculation is done for each ProjectID.
My question is how to formulate this in a SQL query? My first thought was to create a recursive CTE, but I am actually not sure it is the right way proceed. Recursive CTE is (from my understanding) made for handling more of hierarchical like structure, which this isn't really.
My other thought was to calculate the SUM(R_t-1) using windowed functions, ie SUM OVER (PARITION BY ORDER BY) with a LAG, but the recursiveness really gives me trouble and I run my head against the wall when I am trying.
Below a query for creating the input data
CREATE TABLE [dbo].[InputForRecursiveCalculation]
(
[Time] int NULL,
ProjectID [int],
ContractValue float,
ContractHours float,
HoursRegistered float,
RemainingHours float
)
GO
INSERT INTO [dbo].[InputForRecursiveCalculation]
(
[Time]
,[ProjectID]
,[ContractValue]
,[ContractHours]
,[HoursRegistered]
,[RemainingHours]
)
VALUES
(0,101,500000,500,65,500),
(1,101,500000,500,100,435),
(2,101,500000,500,85,335),
(3,101,500000,500,69,250),
(4,101,450000,650,100,331),
(5,101,450000,650,80,231),
(6,101,450000,650,90,151),
(7,101,450000,650,45,61),
(8,101,450000,650,16,16),
(0,110,120000,90,10,90),
(1,110,120000,90,10,80),
(2,110,130000,90,10,70),
(3,110,130000,90,10,60),
(4,110,130000,90,10,50),
(5,110,130000,90,10,40),
(6,110,130000,90,10,30),
(7,110,130000,90,10,20),
(8,110,130000,90,10,10)
GO
For those of you who dare downloading something from a complete stranger, I have created an Excel file demonstrating the calculation (please download the file as you will not be to see the actual formula in the HTML representation shown when first clicking the link):
https://www.dropbox.com/s/3rxz72lbvooyc4y/Calculation%20example.xlsx?dl=0
Best regards,
Victor
I think it will be usefull for you. There is additional column SumR that stands for sumarry of previest rows (for ProjectID)
;with recu as
(
select
Time,
ProjectId,
ContractValue,
ContractHours,
HoursRegistered,
RemainingHours,
cast((ContractValue - 0)*HoursRegistered/RemainingHours as numeric(15,0)) as R,
cast((ContractValue - 0)*HoursRegistered/RemainingHours as numeric(15,0)) as SumR
from
InputForRecursiveCalculation
where
Time=0
union all
select
input.Time,
input.ProjectId,
input.ContractValue,
input.ContractHours,
input.HoursRegistered,
input.RemainingHours,
cast((input.ContractValue - prev.SumR)*input.HoursRegistered/input.RemainingHours as numeric(15,0)),
cast((input.ContractValue - prev.SumR)*input.HoursRegistered/input.RemainingHours + prev.SumR as numeric(15,0))
from
recu prev
inner join
InputForRecursiveCalculation input
on input.ProjectId = prev.ProjectId
and input.Time = prev.Time + 1
)
select
*
from
recu
order by
ProjectID,
Time
RESULTS:
Time ProjectId ContractValue ContractHours HoursRegistered RemainingHours R SumR
----------- ----------- ---------------------- ---------------------- ---------------------- ---------------------- --------------------------------------- ---------------------------------------
0 101 500000 500 65 500 65000 65000
1 101 500000 500 100 435 100000 165000
2 101 500000 500 85 335 85000 250000
3 101 500000 500 69 250 69000 319000
4 101 450000 650 100 331 39577 358577
5 101 450000 650 80 231 31662 390239
6 101 450000 650 90 151 35619 425858
7 101 450000 650 45 61 17810 443668
8 101 450000 650 16 16 6332 450000
0 110 120000 90 10 90 13333 13333
1 110 120000 90 10 80 13333 26666
2 110 130000 90 10 70 14762 41428
3 110 130000 90 10 60 14762 56190
4 110 130000 90 10 50 14762 70952
5 110 130000 90 10 40 14762 85714
6 110 130000 90 10 30 14762 100476
7 110 130000 90 10 20 14762 115238
8 110 130000 90 10 10 14762 130000
Table name: student
Stu_id Stu_Name
1 ani
2 sudipta
3 debayan
4 achinto
5 dipankar
Table name: trans
stu_id mon amount
1 JANU 500
1 FEB 600
1 APR 500
3 JANU 600
3 MAR 700
result will be below
STU_ID STU_NAME Defaulter month
1 ani MAR,MAY,JUNE,JULY,AUG,SEP,OCT,NOV,DEC
2 SUDIPTA JANU.FEB,MAR,APR,MAY,JUNE,JULY,AUG,SEP,OCT,NOV,DEC
3 debayan FEB,APR,MAY,JUNE,JULY,AUG,SEP,OCT,NOV,DEC
4 achinto JANU.FEB,MAR,APR,MAY,JUNE,JULY,AUG,SEP,OCT,NOV,DEC
5 dipankar JANU.FEB,MAR,APR,MAY,JUNE,JULY,AUG,SEP,OCT,NOV,DEC