I have dataset with 00:00:00,00:00:15...
how to set it to be the timePeriod Expression to show one day's time from 00:00:00 to 23:59:59
i put (Date)new SimpleDateFormat("HH:mm").parse($F{time}) into the timePeriod Expression
but the chart just show one time point
If you don't have gaps you can use Line chart like DeGriz's link to Tarnschaf's answer.
If you may have gaps or would like to summarise the data ensure you use <timeSeriesDatasettimePeriod="Second"> or perhaps timePeriod="Minute" otherwise it tends to default to something large like a year, hence one data point.
THE JASPERREPORTS ULTIMATE GUIDE: Time Period Expression
This expression returns a java.util.Date value from which the engine will extract the
corresponding time period depending on the value set for the timePeriod attribute
mentioned earlier in the Time Series dataset. For instance, if the chart is about yearly
data, the engine will extract only the year from the date value, or if you are gathering
monthly data, the engine will use only the month value from the date object returned by
this expression.
I think you may also be asking to set the Min and Max for the axis to exactly one day, for this I believe you can use <domainAxisMinValueExpression> and <domainAxisMaxValueExpression>
Related
Good day all,
I am trying to filter todays result in SQL table to a collection in powerapps. The column "dt" represents the column in sql of datetime type.
This is my powerapps filter:
ClearCollect(myCollectionName, Filter(myDatasource, Text(dt,"dd/mm/yyyy") = Text(Now(),"dd/mm/yyyy" )));
Seems like the collection is still empty even there is data for today in sql. May I know if my approach is the correct way in filtering?
Short answer: the data is likely being changed based on the client time zone. To fix it, you can update it by applying the time zone offset to the data from the SQL table, something along the lines of:
ClearCollect(
myCollectionName,
Filter(
myDatasource,
Text(DateAdd(dt, TimeZoneOffset(dt), Minutes), "dd/mm/yyyy") =
Text(Now(), "dd/mm/yyyy")))
Long(er) answer: the datetime type in SQL Server represents an absolute value of date and time. For example, the value '2021-12-23 09:30:00' represents 9:30 in the morning of the 23rd day of December, 2021 - at any part of the world. The date/time type in Power Apps, however, represents a point in time, typically referring to the local time where the app is being executed (or created). For example, if I selected that value and I'm in the US Pacific Time Zone (UTC-08:00), that would represent the same value as if someone in London (UTC+00:00) selected 2021-12-23 17:30:00. Since the two types represent different concepts, we may have mismatches like you are facing. To fix this, we can either use a type in SQL Server that has the same semantics as Power Apps (for example, 'datetimeoffset'), or adjust the time when it is being transferred between SQL and Power Apps.
The blog post at https://powerapps.microsoft.com/en-us/blog/working-with-datetime-values-in-sql explains in more details how to work with date/time values in SQL and Power Apps.
I created a rudimentary Google Form to track my win rate at Starcraft. The first column on the resulting Google Sheet is Timestamp created by the form.
I have another column that has my win-loss, and I am able to calculate my percentage for the entire sheet (all games). However, I want to be able to see my daily win rate, and I can't figure out the correct way to go about it.
I tried COUNTIF, COUNTIFS, with TODAY() and I was able to count the games for a certain day, but I don't know how to use it to tie in with my win-loss column. What I currently do is adjust my Daily formula to specify today's date before playing. I was hoping I won't need to do this.
Please see Win-Loss Stats Sheet
Solution:
You can extend your formula to compare against the date in column A:
=(COUNTIFS(D2:D, "Win", ARRAYFORMULA(INT(A2:A)),TODAY())/((COUNTIFS(D2:D, "Win",ARRAYFORMULA(INT(A2:A)),TODAY()))+(COUNTIFS(D2:D, "Loss",ARRAYFORMULA(INT(A2:A)),TODAY()))))
The additional condition would be ARRAYFORMULA(INT(A2:A)),TODAY(), which converts the timestamps into dates and compares them to today's date.
Sample Output:
I am working on a large nested IF statement that checks several validation points for each row of my sheet. There are several date validations, including chronological order and certain fields not being future dates. However, our system requires that if we must null any dates for processing, that date becomes 1/1/2500, and no matter what I do I cannot seem to get the formula to ignore this date when accounting for future dates or chronology.
//The date cannot be later than the current date - I want this to ignore 1/1/2500
IF(K1<>1/1/2500,"",IF(AND(K1>TODAY()),"Date A cannot be future date",""))
//The two dates must be in chronological order, also ignoring 1/1/2500
IF(U1<>1/1/2500,"",IF(AND(U1>AA1,AA1),"Date A, Date B should be in chronological order",""))
The above approach does not seem to recognize 1/1/2500, even though I got it to work with other dates.
I also tried going with >12/31/2099 (ignore any date greater than 12/31/2099) but it just ignores every date.
Any help would be appreciated.
It looks as though it is failing because K1 is compared to 12/31/2099.
If you use an expression like this in a formula, it will interpret it as an arithmetic expression 12 divided by 31 divided by 2099, which is a very small number, so the greater than test will always be true.
Try starting the formula with Date to convert a year, month, and day into a date.
If(K1>date(2099,12,31)
and you should get the right answer.
See my previous answer for Excel.
Let's say I have a date dimension and from my business requirements I know that the most granular I would need to go is to examine the specific day of the month that an event occurred.
The data I am given provides me with the exact time that an event occurred (YYYY-MM-DD HH:MM:SS). I have two opitons:
Before loading the data into the date dimension, slice the HH:MM:SS from the date.
Create the time attributes in my date dimension and insert the full date time.
The way I see it, I should go with the option 1. This would remove redundant data and save some space. However, if I go with option 2, should the business requirements ever change or if my manager suddenly wants to be more granular I wouldn't need to modify my original design. Which option is more commonly used? Are there more options that I did not consider?
Update - follow up question
I receive new data every month. If I used a pre built date dimension with all the dates would I then need to run my script every month to populate the table with new dates of that month or would I have a continuous process where by every day insert into the table one row, which would be that date?
I would agree with you and avoid option 2. A standard date dimension table is at the individual date level. If you did need to analyse by time of day, you could create an additional time of day dimension at the level of a second in a single day, and link to that from your fact table.
Your date dimension should be created by script automatically, rather than from the dates that events occurred. This allows you to analyse across a range of events from other facts, and on dates where no events occur, using a standard, prebuilt dimension.
I would also include the full date/time stamp as a column in the fact table, along with the 'DateKey' to the dimension table. This would allow you some visibility/analysis of the timestamp, you would not lose the data, and would still allow you to analyse by the date dimension.
Update - follow up question
Your pre-built date dimension (the standard way of doing it) would usually contain some dates in the future. There's no reason not to, for example, include another 5 years of dates in the table. But if you'd like it to gradually grow over time, you could have a script that is run once a day, once a month, or once a year to add new dates. Its totally up to you! There are many example scripts for building date dimensions- just google date dimension script. They exist for the language of your choice, e.g. SQL, C#, Power Query, etc.
I have a data set in which month and year are in one variable and come in the form 200801 which equates to 2008, January. How can I create a SAS date from this integer?
I would like something in the form of Jan 2008 - anything so that SAS recognizes it as a date, as I then need to subtract this value from service date to find out how much time has elapsed since enrollment into the dataset until date of service.
Please also keep in mind that this is a variable, and I have thousands of observations. So I also need the data step/ function to do this for the entire variable.
Any help is appreciated!
You need to put it to a character variable, then input back to numeric. You can do that pretty easily.
date_var = input(put(date_var_orig,6.)||'01',yymmdd8.);
You can also do it this way:
date_var = mdy(mod(date_var_orig,100),1,floor(date_var_orig/100));
Both assume you want the day to equal 1; make a choice there if you want something else (like end of month or middle of month).