Here is the problem I am working on:
You are to develop a menu-driven program that will allow the analyses of data from the file Patient_Data.txt using the following equations:
Half-Life Equations
Ct = C0e^-kt
t½ = ln(2)/k
where:
Ct is the concentration in ug/L at time t
C0 is the initial concentration in ug/L
t is the time in hrs
k is the time constant (1/hrs)
t½ is the half-life in hrs
The user of the program must be able to obtain the average half-life (to 2 decimal places) along with the number of measurements used to calculate the average for any of the 5 patients for which data has been collected.
The program must also be able to display the 2 patient numbers and averages of the patients that have the highest half-life average values.
A menu must be used to select the different options with an additional option for Exit. The program must run until exit is selected by the user.
The program must be designed using functions.
A function called analyzeData must take as input the patient number and must return both the average half-life and the number of measurements in the average for the input patient number.
A separate function called halfLife is to be used for calculating the t½ (half-life) based on C0 (initial concentration), Ct (concentration at time t) and t (time) that are in the data file.
A third function called highest2halfLifes must also be used to determine the two patients with the longest average half-life from the five different patients. All four values (patient1, halfLife1, patient2, halfLife2) must be returned to the main function.
The following data file Patient_Data.txt lists values for C0, Ct, and t, respectively (Patient Data)
1 325 160 2.0
1 600 100 6.2
2 325 220 1.0
3 600 200 4.4
4 325 100 3.0
4 325 88 3.2
2 600 200 3.3
2 325 100 3.3
4 600 210 3.4
5 325 105 3.5
1 600 110 6.0
3 325 100 3.1
2 600 120 5.5
2 600 125 5.5
5 120 60 2.2
2 325 100 3.4
Related
I am trying to create a list of the 99th and 1st percentiles. Rather than a single percentile for today. I wanted percentiles for 500 days each using the prior 500 days. The functions I was using for this are the following
swin:{[f;w;s] f each { 1_x,y }\[w#0;s]}
percentile:{[x;y] y (100 xrank y:asc y) bin x}
swin[percentile[99;];500;List].
The issue I come across is that the 99th percentile calculates perfectly, but the 1st percentile makes the entire list = 0. a bit lost as to why it would do that. suggestions appreciated!
What's causing the zeros is two-fold:
What behaviour do you want for the earliest 500 days when there isn't 500 days of history to work with? On day 1 there's only 1 datapoint, on day 2 only 2 etc. Only on the 500th day is there 500 days of actual data to work with. By default that swin function fills the gaps with some seed value
You're using zero as that seed value, aka w#0
For example a 5 day lookback on each date looks something like:
q)swin[::;5;1 2 3 4 5]
0 0 0 0 1
0 0 0 1 2
0 0 1 2 3
0 1 2 3 4
1 2 3 4 5
You have zeros until you have data, so naturally the 1st percentile will pick up the zeros for the first roughly 500 dates.
So then you can decide to seed with a different value, or else possibly exclude zeros from your percentile function:
q)List:1000?1000
q)percentile:{[x;y] y (100 xrank y:asc y except 0) bin x}
q)swin[percentile[1;];500;List]
908 360 360 257 257 257 90 90 90 90 90 90 90 90...
If zeros are a legitimate value in your list and can't be excluded then maybe seed the swin with some other value that you know won't be in the list (negatives? infinity? null?) and then exclude that seed from the percentile function.
EDIT: A final alternative is to use a different sliding window function which doesn't fill gaps with a seed value, e.g.
q)swin2:{[f;w;s] f each(),/:{neg[x]sublist y,z}[w]\[s]}
q)swin2[::;5;1 2 3 4 5]
,1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
q)percentile:{[x;y] y (100 xrank y:asc y) bin x}
q)swin2[percentile[99;];500;List]
908 908 908 908 908 908 908 908 908 908 908 959 959..
q)swin2[percentile[1;];500;List]
908 360 360 257 257 257 90 90 90 90 90 90 90 90 90..
I want to query a number of rows from one sheet into another sheet, and to the right of this row add a column based on one of the queried columns. Meaning that if column C is "Il", I want to add a column to show 0, otherwise 1 (the samples below will make it clearer.
I have tried doing this with Query and Arrayformula, without query, with Filter and importrange. An example of what I tried:
=query(Data!A1:AG,"Select D, E, J, E-J, Q, AG " & IF(AG="Il",0, 1),1)
Raw data sample:
Captured Amount Fee Country
TRUE 336 10.04 NZ
TRUE 37 1.37 GB
TRUE 150 4.65 US
TRUE 45 1.61 US
TRUE 20 0.88 IL
What I would want as a result:
Amount Fee Country Sort
336 10.04 NZ 1
37 1.37 GB 1
150 4.65 US 1
45 1.61 US 1
20 0.88 IL 0
try it like this:
=ARRAYFORMULA(QUERY({Data!A1:Q, {"Sort"; IF(Data!AG2:AG="IL", 0, 1)}},
"select Col4,Col5,Col9,Col5-Col9,Col17,Col18 label Col5-Col9''", 1))
I have a dataset OvertimeHours with EMPLID, checkdate and NumberOfHours (and other fields). I need a running total NumberOfHours for each employee by checkdate. I tried using the Quick Measure option but that only allows for a single column and I have two. I do not want the measure to recalculate when filters are applied. Ultimately what I am trying to do is identify the records for the first 6 hours of overtime worked on each check so that they can get a category of OCB and all overtime over the first 6 hours is OTP and it does not have to be exact (as demonstrated in the output below). I have only been working with Power BI for about a month and this is a pretty complex (for me) formula to figure out...
EMPLID CheckDate WkDate NumberOfHours RunningTotal Category
124 1/1/19 12/20/18 5 5 OCB
124 1/1/19 12/21/18 9 14 OTP
125 1/1/19 12/20/18 3 3 OCB
125 1/1/19 12/20/18 2 5 OCB
125 1/1/19 12/22/18 2 7 OTP
124 1/15/19 1/8/19 3 3 OCB
*Edited to add the WkDate.
Edit:
I have tweaked my query so that I have the running total and a sequential counter now:
Using the first 12 records, I am looking to get the following results:
I can either do it in a query if that is the easiest way or if there is a way to use DAX in PowerBI with this dataset now that I have the sequential piece, I can do that too.
I got it in the query:
select r.CheckDate,
r.EMPLID,
case
when PayrollRunningOTHours <= 6
then PayrollRunningOTHours
else 6
end as OCBHours,
case
when PayRollRunningOTHours > 6
then PayRollRunningOTHours - 6
end as OTPHours
from #rollingtotal r
inner
join lastone l
on r.CheckDate = l.CheckDate
and r.EMPLID = l.EMPLID
and r.OTCounter = l.lastRec
order by r.emplid,
r.CheckDate,
r.OTCounter
I am currently trying to create a report that shows how customers behave over time, but instead of doing this by date, I am doing it by customer age (number of months since they first became a customer). So using a date field isn't really an option, considering one customer may have started in Dec 2016 and another starts in Jun 2017.
What I'm trying to find is the month-over-month change in units purchased. If I was using a date field, I know that I could use
[Previous Month Total] = CALCULATE(SUM([Total Units]), PREVIOUSMONTH([FiscalDate]))
I also thought about using EARLIER() to find out but I don't think it would work in this case, as it requires row context that I'm not sure I could create. Below is a simplified version of the table that I'll be using.
ID Date Age Units
219 6/1/2017 0 10
219 7/1/2017 1 5
219 8/1/2017 2 4
219 9/1/2017 3 12
342 12/1/2016 0 500
342 1/1/2017 1 280
342 2/1/2017 2 325
342 3/1/2017 3 200
342 4/1/2017 4 250
342 5/1/2017 5 255
How about something like this?
PrevTotal =
VAR CurrAge = SELECTEDVALUE(Table3[Age])
RETURN CALCULATE(SUM(Table3[Units]), ALL(Table3[Date]), Table3[Age] = CurrAge - 1)
The CurrAge variable gives the Age evaluated in the current filter context. You then plug that into a filter in the CALCULATE line.
I have used SAS PROC RANK to rank a population based on score and create groups of equal size. I would like to create groups such that there is a minimum number of target variable (Goods and Bads) in each bin. Is there a way to do that using PROC RANK? I understand that the size of each bin would be different.
For example in the table below, I have created 10 groups based on a certain score. As you can see the Non cures in the lower deciles are sparse. I would like to create groups such there there are at least 10 Non cures in each group.
Cures and Non cures are based on same variable: Cure = 1 and Cure = 0.
Decile cures non cures
0 262 94
1 314 44
2 340 19
3 340 13
4 353 10
5 373 5
6 308 3
7 342 3
8 440 4
9 305 3