Hello this is probably very basic although I can not find a similar question and have tried many similar fixes found here.
Anyway im trying to transfer a hourly time series from xcell as .csv to R and create a bar plot that accurately uses the hourly data I have. so far r is thinking that what I have is consecutive numbers and ignores time
heres my data:
time1 chrono1
22:00 0
22:30 0
23:00 0
23:30 0
0:00 1.1
0:30 2.6
1:00 4.8
1:30 7
2:00 10.8
2:30 14
3:00 15.1
3:30 12.58
4:00 10
4:30 7
5:00 4.9
5:30 3.8
6:00 2.6
6:30 2.2
7:00 1.25
7:30 1.18
8:00 1
8:30 0.8
9:00 0.8
9:30 0.3
10:00 0
10:30 0
heres the base code im using:
ggplot(hourly, aes(x=time1,y=chrono1)) +
geom_bar(stat='identity')
BPlot
It looks like there are a couple of issues. First if you want a bar for each time convert your time to a factor using as.factor(). Then instead of geom_barplot use geom_col(). That should get you mostly there and then you can change the aesthetics of the plot as you see fit
Related
I have set 90 hours to complete a job.
Every time I work on the job I want to subtract that time from 90 (90 - time worked)
This is to be done in a Libreoffice spreadsheet
I have some data saved as a tsv and the times it saves are as follow:
16984 = 16 second 984 milliseconds
214032 = 2 minutes 14 seconds, 032 milliseconds
I've looked at the https://www.iso.org/iso-8601-date-and-time-format.html but it's not clear about durations
I don't think this is UNIX time either
It should from an https://imotions.com/ software
Given a set of operations that have start and end times and require a number of processors, and a set of processors that are available at start and end times does a polynomial algorithm exist to determine if all the tasks can be run? As a follow-up does a polynomial algorithm exist that returns a possible execution?
For example:
O1: 7:00 AM to 8:00 AM - req. 2 × Processors
O2: 8:00 AM to 9:00 AM - req. 2 × Processors
O3: 7:00 AM to 9:00 AM - req. 2 × Processors
Can be run on the following processors
P1: 7:00 AM to 9:00 AM - runs O1 and O2
P2: 7:00 AM to 9:00 AM - runs O1 and O2
P3: 7:00 AM to 9:00 AM - runs O3
P4: 7:00 AM to 9:00 AM - runs O3
But cannot be run on the following processors:
P1: 7:00 AM to 8:00 AM
P2: 8:00 AM to 9:00 AM
P3: 7:00 AM to 9:00 AM
P4: 7:00 AM to 9:00 AM
Note: it isn't possible to switch processors for an operation.
I believe it might be a related to either the Job Shop Scheduling (JSP) and Nurse Scheduling Problem (NSP) however both seem slightly different.
For both JSP and NSP the key difference is that there is no min / max requirement (and we don't care about the optimal solution - just if a solution exists).
You are interested in a small variation of the Fixed Job Scheduling Problem : each job has a fixed start and end time and a value and the aim is to maximizes the value of jobs completed by identical machines (in your case, the value is 1 for any job). The only difference is that you have an interval of availability for the processors. Since you just want to know if it is possible to assign all the jobs, you can add fictive jobs on the unavailable slots of your processors. In your second example, you can add a job from 8 to 9, and another from 7 to 8.
You hence can solve this problem in polynomial time, by slightly adapting the algorithm provided in the attached article.
I have a dbms_scheduler job which has to run every 4 hours, in timezone 'Europe/Berlin'
My question is: what happens on days with a change in daylight saving time?
Let's say, last runtime was 01:00 AM. Not time either is set from 02:00AM to 03:00AM or from 03:00AM to 02:00AM.
Is the next runtime of my job after 3 hours in the first and after 5 hours in the second case or will it be just after 4 hours, regardless of the change in daylight saving time?
I'm trying to convert the normal 24 hour system to a 20 hour system in JavaScript or html
there seems to be problems and I don't know how to fix them, the program code as a whole works ok but it's not accurate in the area of displaying the proper time
can someone help me.
24hrs per day to 20hrs
60 minutes per hour to 40 minutes per hour
60 seconds per minute to 80 seconds per minute
1000 milliseconds per second to 1350 milliseconds per second
I have been working with the code that is supposed to get the milliseconds from 1/1/1970 to make things hopefully simple but like I said the program isn't working quite right, I do have a table that lets me know what normal time would be at each changed hour but that's all the info I have
Check this Fiddle:
http://jsfiddle.net/z4s7j9vL/1/
My approach was to get the timestamp difference between the current time and midnight of the same day:
millis = ts - clone.getTime();
This way you get how many milliseconds have passed this day and you can do your conversion from there. This is limited to converting time only, but if months and years followed the same principles you could just convert the same way from the current timestamp.