I am working with many signals; each one in a time series but is too many and, I need to make more than 1000 but, I am not sure how to implement it because I not only need the plots but the values of output for each spectrogram stored in a file or an R object. I am sorry I don't have an approach. Can anyone help out, please?
I'm very new to R and pretty basic with analyses generally. I successfully ran a regression in R, but a lot of my data are missing. I'm fine with that because R just ignores the missing observations in the analyses and shows me the dfs in the summary. My problems is that I'd like to look more into the observations that are included in the analyses, but I'm not sure how to do that.
I tried to do na.omit, but R created a dataset with far fewer observations than it used in the regressions, so I think that takes it too far.
Basically, I'm trying to get the ages for the respondents that were included in the final analyses, not just the ages of the entire sample, many of whom were not included in the analyses.
Any advice you can give me would be very appreciated!! Please let me know if you need more information.
Thank you!
Edited to include Screenshot of data.
We have a lot of types of plots available in R. And every single time I get a dataset, I have to think for a long time that which type of plot I should use to plot my dataset in order to get information I want (I'm a beginner of R). I don't know whether it's related to my math and stats knowledge or just not familiar with R tech skills. Anybody can tell me the reasons and how to improve that? Thanks many in advance.
I would like to know how to upload a data set from R packages to winbugs.
In particular, "LearnBayes" package in R has too many data sets. I would like to use one of them in Winbugs.
Can anyone help me with this?
I came across this link because I have no idea what WinBugs data is suppose to look like but I don't know if it works. It's an R Function that supposedly changes the typical dataset into this list thing and I got the function working but still not able to get the dataset working but I'm really stupid so you might have better luck.
I am beginner in R. So, I am confused about the title of my question. sorry for that. I am trying to explain..
Professor gave me a NetCDF atmospheric data file(18.3MB).this file has 8 dimension and 8 variable. i have to work with 4 variable. every variable(time,site number,urban site,pm10) has 683016 data. suppose,
Urban site number:[2,5],
site number:[1,2,3,4,5,6],
time:[1-3-2012,2-3-2012....](hourly data(24) has taken in each day ),
pm10:[1,2,3,4,5,6.......](different for every hourly data with some missing value)
I have to manage this data set only for urban site and 1-3-2012(actually I have to make this spatio-temporal data to spatial data).I want my final data set like this:
Colum 1(time): 1-3-2012,1-3-2012,1-3-2012,1-3-2012,1-3-2012,1-3-2012
colum 2(Urban site number): 2,2,2,5,5,5
colum 3(pm10 value):1,2,3,NA,4,5,
As I only know very basic commands of R so I cant understand how can I solve this problem. Even I don't under stand How can I find any example of this type of problem in internet.
so, please give me some suggestion or link about what I have to learn to solve this problem in R. Please, help me out?
I think you're trying to reshape the dataset but i'm afraid i do not see how your current dataset looks like.
Could you elaborate more on what your dataset looks like right now?
There are packages that help reshaping such as {reshape} or {plyr}. But i need more detail to suggest which one you should use.