Re: [R] recommended combo of apps for new user?
--- hadley wickham <[EMAIL PROTECTED]> wrote: > On 8/18/07, John Kane <[EMAIL PROTECTED]> wrote: > > I'm just starting to get a grasp on how R works so > > don't take my words too seriously but have a look > at > > http://addictedtor.free.fr/graphiques/ for some > idea > > of what R can do for publication quality graphics. > It > > is always possible that you might need another > > graphics package as well but I think it unlikely. > > I may be in the minority, but I really don't like > the R graph gallery. > To my eye it largely provides examples of what you > _shouldn't_ do > with graphics (and also seems rather unloved at the > moment, given the > large number of spam keywords). It fails to provide > examples of using > graphics to gain insight into your data and mainly > focuses on drawing > pretty (ugly) pictures. > > Unfortunately there aren't many better resources at > the moment. > Deepayan Sarkar is working on a lattice book, and > hopefully he will > make the plots available on his website as well. > I'm also working on > a book for my ggplot2 package > (http://had.co.nz/ggplot2) but that > won't be finished until next year. For interactive > graphics, the > GGobi book (http://www.ggobi.org/book/) is very > close to being > published, and provides details about the R-GGobi > link as well as many > techniques for gaining insight into your data > interactively. Another > option is the Graphics of Large Dataset book > (http://rosuda.org/gold/) > which provides a wider survey of state of the art in > interactive > graphics for large datasets. > > Hadley > I don't disagree in a number of cases but it is a good example of the myriad of things that one can do with R graphics even if you may not want to! And in some cases, expecially in the business world, jazzing up a graphic may be needed even if it does not improve the actual understanding of the data. In the context of the OP's question about graphical capabilites for publication quality output I think the gallery is not a bad illustration of R's versitility. Thanks for the book references. Now just to pry them loose from wthe library; well the Cook & Swayze one isn't through cataloging yet. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
On 8/18/07, John Kane <[EMAIL PROTECTED]> wrote: > I'm just starting to get a grasp on how R works so > don't take my words too seriously but have a look at > http://addictedtor.free.fr/graphiques/ for some idea > of what R can do for publication quality graphics. It > is always possible that you might need another > graphics package as well but I think it unlikely. I may be in the minority, but I really don't like the R graph gallery. To my eye it largely provides examples of what you _shouldn't_ do with graphics (and also seems rather unloved at the moment, given the large number of spam keywords). It fails to provide examples of using graphics to gain insight into your data and mainly focuses on drawing pretty (ugly) pictures. Unfortunately there aren't many better resources at the moment. Deepayan Sarkar is working on a lattice book, and hopefully he will make the plots available on his website as well. I'm also working on a book for my ggplot2 package (http://had.co.nz/ggplot2) but that won't be finished until next year. For interactive graphics, the GGobi book (http://www.ggobi.org/book/) is very close to being published, and provides details about the R-GGobi link as well as many techniques for gaining insight into your data interactively. Another option is the Graphics of Large Dataset book (http://rosuda.org/gold/) which provides a wider survey of state of the art in interactive graphics for large datasets. Hadley __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
Thanks so much for the many responses on and off this email list! I think it's helped me reach a resolution. I'm going to use R on my current small project for something relatively self-contained, such as some final tests and graphics. I figure this will help me learn some basics about interacting with R without getting too bogged down in setting up a new database system -- which sounds like a job all on its own. After I understand a bit more about R's capabilities I'll ease into the database part. Cheers, Martin __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
Thanks so much for the many responses on and off this email list! I think it's helped me reach a resolution. I'm going to use R on my current small project for something relatively self-contained, such as some final tests and graphics. I figure this will help me learn some basics about interacting with R without getting too bogged down in setting up a new database system -- which sounds like a job all on its own. After I understand a bit more about R's capabilities I'll ease into the database part. Cheers, Martin On 8/19/07, Gabor Grothendieck <[EMAIL PROTECTED]> wrote: > > Regarding RODBC vs. DBI-based packages (RSQLite, RMySQL, etc.) its > my perception, possibly mistaken, that apart from any consideration of > the R packages themselves, ODBC (which originated in the Windows world) > is more widely used on Windows than UNIX. Also ODBC has the problem > that one must configure it which puts an extra step into the > process. Clear > documentation on how to do such ODBC configuration may be difficult to > find. > > On the other hand the RODBC package itself seems to be maintained > very well and is typically available for new versions of R before the > DBI-based packages. > > On 8/19/07, Prof Brian Ripley <[EMAIL PROTECTED]> wrote: > > Some additional comments on the DBMS front. > > > > (a) SPSS is not a DBMS, so it is not clear that you need this. But if > you > > do and are storing valuable data in a DBMS a lot of further questions > come > > into play, like how you are going to do backups. I'd say PostgreSQL was > > really only for professional-level administrators. My sysadmins > recommend > > MySQL for most people. We do also run PostgreSQL and they find it a lot > > trickier to maintain. > > > > 'dozens of columns and thousands of rows' is not big. A data frame with > > 50 columns and 5000 rows would only take 2Mb to store, and R will easily > > handle 100x with 4GB of RAM (and if you have less, get 4GB). So storing > > data in .rda (R's save() format) is most likely viable. R's indexing > etc > > operations make it good at data manipulation, and using a DBMS will > > involve learning SQL, a non-trivial cost. > > > > (b) You have a choice of interfaces to a DBMS, RODBC and the DBI+ > family, > > e.g. DBI+RMySQL and DBI+RSQLite. I'm biased, but I find RODBC more > > intuitive, and many people have reported it to be faster. If all you > want > > is non-permanent storage for manipulation of large data sets, consider > > also SQLiteDF. > > > > On Sat, 18 Aug 2007, Duncan Murdoch wrote: > > > > > Martin Brown wrote: > > >> [i sent this message earlier but apparently should have sent it plain > > >> text, as follows..] > > >> > > >> Hi there, > > >> > > >> I would like some advice, not so much about how to use R, but about > > >> software that I need to complement R. I've rooted around in the > FAQ's > > >> and done a few searches on this mailing list but haven't quite found > > >> the perspective I need. > > >> > > >> I am an experienced data analyst in my field (forest ecology and > > >> ecological monitoring) but new to R. I am a long time user of SPSS > and > > >> have gotten pretty handy with it. However, I am frustrated with SPSS > > >> for several reasons: There's the cost (I'm a freelancer; I pay for > my > > >> software myself); the Windows dependence (I use Kubuntu as my usual > > >> OS now, and switching back and forth is a pain); the horrible > > >> inefficiency when I do certain types of file manipulations; and the > > >> inability to do the kind of publication-quality graphs I want... I've > > >> usually ended up using a commercial graphing program (another source > > >> of expense and limitation). > > >> > > >> I'd like to switch to using R on Kubuntu, for all those reasons. In > > >> addition I think the mathematical formality that R encourages might > be > > >> good for me. > > >> > > >> However, reviewing the FAQ's on the R project web site makes me > > >> realize that I've been using SPSS as three kinds of software really: > > >> a DBMS; a statistical analysis package; and a graphing package. It > > >> looks like moving to R might involve learning three kinds of > software, > > >> not just one. I wonder: > > >> > > >> 1) What open-source DBMS works most seamlessly with R? I have seen > > >> MySQL recommended but wonder if there are alternatives. I sometimes > > >> need to handle big data files. In fact a lot of my work involves > > >> exploratory and descriptive analyses of rather large and messy > > >> databases from ecological monitoring, rather than statistical tests > > >> per se. In SPSS the data files I have been generating have dozens of > > >> columns and thousands of rows, often with value and variable labels > > >> helpful for documenting my work. > > > > See above. > > > > > > > > I think you won't find much difference in the R interface between > MySQL, > > > PostgreSQL, or SQLite. The choice should be made based on the > qualities > > > of the data
Re: [R] recommended combo of apps for new user?
Regarding RODBC vs. DBI-based packages (RSQLite, RMySQL, etc.) its my perception, possibly mistaken, that apart from any consideration of the R packages themselves, ODBC (which originated in the Windows world) is more widely used on Windows than UNIX. Also ODBC has the problem that one must configure it which puts an extra step into the process. Clear documentation on how to do such ODBC configuration may be difficult to find. On the other hand the RODBC package itself seems to be maintained very well and is typically available for new versions of R before the DBI-based packages. On 8/19/07, Prof Brian Ripley <[EMAIL PROTECTED]> wrote: > Some additional comments on the DBMS front. > > (a) SPSS is not a DBMS, so it is not clear that you need this. But if you > do and are storing valuable data in a DBMS a lot of further questions come > into play, like how you are going to do backups. I'd say PostgreSQL was > really only for professional-level administrators. My sysadmins recommend > MySQL for most people. We do also run PostgreSQL and they find it a lot > trickier to maintain. > > 'dozens of columns and thousands of rows' is not big. A data frame with > 50 columns and 5000 rows would only take 2Mb to store, and R will easily > handle 100x with 4GB of RAM (and if you have less, get 4GB). So storing > data in .rda (R's save() format) is most likely viable. R's indexing etc > operations make it good at data manipulation, and using a DBMS will > involve learning SQL, a non-trivial cost. > > (b) You have a choice of interfaces to a DBMS, RODBC and the DBI+ family, > e.g. DBI+RMySQL and DBI+RSQLite. I'm biased, but I find RODBC more > intuitive, and many people have reported it to be faster. If all you want > is non-permanent storage for manipulation of large data sets, consider > also SQLiteDF. > > On Sat, 18 Aug 2007, Duncan Murdoch wrote: > > > Martin Brown wrote: > >> [i sent this message earlier but apparently should have sent it plain > >> text, as follows..] > >> > >> Hi there, > >> > >> I would like some advice, not so much about how to use R, but about > >> software that I need to complement R. I've rooted around in the FAQ's > >> and done a few searches on this mailing list but haven't quite found > >> the perspective I need. > >> > >> I am an experienced data analyst in my field (forest ecology and > >> ecological monitoring) but new to R. I am a long time user of SPSS and > >> have gotten pretty handy with it. However, I am frustrated with SPSS > >> for several reasons: There's the cost (I'm a freelancer; I pay for my > >> software myself); the Windows dependence (I use Kubuntu as my usual > >> OS now, and switching back and forth is a pain); the horrible > >> inefficiency when I do certain types of file manipulations; and the > >> inability to do the kind of publication-quality graphs I want... I've > >> usually ended up using a commercial graphing program (another source > >> of expense and limitation). > >> > >> I'd like to switch to using R on Kubuntu, for all those reasons. In > >> addition I think the mathematical formality that R encourages might be > >> good for me. > >> > >> However, reviewing the FAQ's on the R project web site makes me > >> realize that I've been using SPSS as three kinds of software really: > >> a DBMS; a statistical analysis package; and a graphing package. It > >> looks like moving to R might involve learning three kinds of software, > >> not just one. I wonder: > >> > >> 1) What open-source DBMS works most seamlessly with R? I have seen > >> MySQL recommended but wonder if there are alternatives. I sometimes > >> need to handle big data files. In fact a lot of my work involves > >> exploratory and descriptive analyses of rather large and messy > >> databases from ecological monitoring, rather than statistical tests > >> per se. In SPSS the data files I have been generating have dozens of > >> columns and thousands of rows, often with value and variable labels > >> helpful for documenting my work. > > See above. > > > > > I think you won't find much difference in the R interface between MySQL, > > PostgreSQL, or SQLite. The choice should be made based on the qualities > > of the database (and I don't know enough about the differences to give a > > recommendaton.) > >> 2) For the purpose of creating publication-quality graphs, do R users > >> typically need to go outside of the R system? If so, what open-source > >> programs would you all recommend? > >> > > R is great for this, but you might need to go outside for some > > specialized stuff (e.g. medical imaging). > > > >> 3) Any other software I need to learn that would make my work in R > >> more productive? (for example, a code editor). > > > > A lot of people are happy with ESS mode in Emacs. > > > > Duncan Murdoch > > > > __ > > R-help@stat.math.ethz.ch mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guid
[R] recommended combo of apps for new user?
> In fact a lot of my work involves exploratory and > descriptive analyses of rather large and messy databases from > ecological > monitoring, rather than statistical tests per se. For the exploratory part of your work you should consider the iPlots package, which provides interactive graphics for R. Antony Unwin __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
Some additional comments on the DBMS front. (a) SPSS is not a DBMS, so it is not clear that you need this. But if you do and are storing valuable data in a DBMS a lot of further questions come into play, like how you are going to do backups. I'd say PostgreSQL was really only for professional-level administrators. My sysadmins recommend MySQL for most people. We do also run PostgreSQL and they find it a lot trickier to maintain. 'dozens of columns and thousands of rows' is not big. A data frame with 50 columns and 5000 rows would only take 2Mb to store, and R will easily handle 100x with 4GB of RAM (and if you have less, get 4GB). So storing data in .rda (R's save() format) is most likely viable. R's indexing etc operations make it good at data manipulation, and using a DBMS will involve learning SQL, a non-trivial cost. (b) You have a choice of interfaces to a DBMS, RODBC and the DBI+ family, e.g. DBI+RMySQL and DBI+RSQLite. I'm biased, but I find RODBC more intuitive, and many people have reported it to be faster. If all you want is non-permanent storage for manipulation of large data sets, consider also SQLiteDF. On Sat, 18 Aug 2007, Duncan Murdoch wrote: > Martin Brown wrote: >> [i sent this message earlier but apparently should have sent it plain >> text, as follows..] >> >> Hi there, >> >> I would like some advice, not so much about how to use R, but about >> software that I need to complement R. I've rooted around in the FAQ's >> and done a few searches on this mailing list but haven't quite found >> the perspective I need. >> >> I am an experienced data analyst in my field (forest ecology and >> ecological monitoring) but new to R. I am a long time user of SPSS and >> have gotten pretty handy with it. However, I am frustrated with SPSS >> for several reasons: There's the cost (I'm a freelancer; I pay for my >> software myself); the Windows dependence (I use Kubuntu as my usual >> OS now, and switching back and forth is a pain); the horrible >> inefficiency when I do certain types of file manipulations; and the >> inability to do the kind of publication-quality graphs I want... I've >> usually ended up using a commercial graphing program (another source >> of expense and limitation). >> >> I'd like to switch to using R on Kubuntu, for all those reasons. In >> addition I think the mathematical formality that R encourages might be >> good for me. >> >> However, reviewing the FAQ's on the R project web site makes me >> realize that I've been using SPSS as three kinds of software really: >> a DBMS; a statistical analysis package; and a graphing package. It >> looks like moving to R might involve learning three kinds of software, >> not just one. I wonder: >> >> 1) What open-source DBMS works most seamlessly with R? I have seen >> MySQL recommended but wonder if there are alternatives. I sometimes >> need to handle big data files. In fact a lot of my work involves >> exploratory and descriptive analyses of rather large and messy >> databases from ecological monitoring, rather than statistical tests >> per se. In SPSS the data files I have been generating have dozens of >> columns and thousands of rows, often with value and variable labels >> helpful for documenting my work. See above. > > I think you won't find much difference in the R interface between MySQL, > PostgreSQL, or SQLite. The choice should be made based on the qualities > of the database (and I don't know enough about the differences to give a > recommendaton.) >> 2) For the purpose of creating publication-quality graphs, do R users >> typically need to go outside of the R system? If so, what open-source >> programs would you all recommend? >> > R is great for this, but you might need to go outside for some > specialized stuff (e.g. medical imaging). > >> 3) Any other software I need to learn that would make my work in R >> more productive? (for example, a code editor). > > A lot of people are happy with ESS mode in Emacs. > > Duncan Murdoch > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
On 8/18/07, Martin Brown <[EMAIL PROTECTED]> wrote: > Hi there, > > I would like some advice, not so much about how to use R, but about software > that I need to complement R. I've rooted around in the FAQ's and done a few > searches on this mailing list but haven't quite found the perspective I > need. > > I am an experienced data analyst in my field (forest ecology and ecological > monitoring) but new to R. I am a long time user of SPSS and have gotten > pretty handy with it. However, I am frustrated with SPSS for several > reasons: There's the cost (I'm a freelancer; I pay for my software > myself); the Windows dependence (I use Kubuntu as my usual OS now, and > switching back and forth is a pain); the horrible inefficiency when I do > certain types of file manipulations; and the inability to do the kind of > publication-quality graphs I want... I've usually ended up using a > commercial graphing program (another source of expense and limitation). > > I'd like to switch to using R on Kubuntu, for all those reasons. In > addition I think the mathematical formality that R encourages might be good > for me. >From a strictly language perspective, mathematical formality is pretty far from R. Its actually quite loose. Underneath there are some Lisp/Scheme ideas but you are not very close to that as a user. > > However, reviewing the FAQ's on the R project web site makes me realize that > I've been using SPSS as three kinds of software really: a DBMS; a > statistical analysis package; and a graphing package. It looks like moving > to R might involve learning three kinds of software, not just one. I > wonder: > > 1) What open-source DBMS works most seamlessly with R? I have seen MySQL > recommended but wonder if there are alternatives. I sometimes need to > handle big data files. In fact a lot of my work involves exploratory and > descriptive analyses of rather large and messy databases from ecological > monitoring, rather than statistical tests per se. In SPSS the data files I > have been generating have dozens of columns and thousands of rows, often > with value and variable labels helpful for documenting my work. Databases. SQLite is the easiest to install since its embedded rather than client/server so I would use that unless your application requires client/server or other features of MySQL. MySQL is probably the most popular of the free data bases so that would be the next one to go with. If you intend to create a commercial application you might want to consider Postgres instead of MySQL as the latter charges for commercial implementations but Postgres does not. Some heavy Postgres users might feel that it should be considered after SQLite rather than MySQL and there is a certain amount of arbitrariness here. See the R packages RSQLite, RMySQL and DBI. The R packages sqldf and SQLiteDF are beginning to blur the boundary between R and the database. > 2) For the purpose of creating publication-quality graphs, do R users > typically need to go outside of the R system? If so, what open-source > programs would you all recommend? Graphics. R should be ok. Check out: http://cran.r-project.org/src/contrib/Views/Graphics.html and also google for R Graphics Gallery > 3) Any other software I need to learn that would make my work in R more > productive? (for example, a code editor). > Other. You need to know a text editor. I use vim but there are many good choices here with ESS being one that is often mentioned. http://www.sciviews.org/_rgui/projects/Editors.html http://ess.r-project.org/ If you intend to write C routines to run with R then, of course, you need to know C. For certain R packages that interface with outside software (tcltk, Rgraphviz, Ryacas, XML, etc.) you will need to know something about the interfaced-to software if you intend to use those packages. For package development you will need to know latex and possibly subversion, i.e. svn, the UNIX screen program, tar and various other UNIX commands. Certain auxilliary programs that come with and are used with R are written in perl although its unlikely you will need to know it. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
I'm just starting to get a grasp on how R works so don't take my words too seriously but have a look at http://addictedtor.free.fr/graphiques/ for some idea of what R can do for publication quality graphics. It is always possible that you might need another graphics package as well but I think it unlikely. About the data bases I don't know really however you might want to have a look at Frank Harrell's Hmic package for things like labels. It also includes SAS and SPSS import funtions as does the foreign package. I'd say you definately need a code editor. I'm on Windows and happy with Tinn-R but for Linux something like http://ess.r-project.org/ seems to be recommended. If you have not already found it Bob Muenchen's R for SAS and SPSS Users http://oit.utk.edu/scc/RforSAS&SPSSusers.pdf may be very helpful. --- Martin Brown <[EMAIL PROTECTED]> wrote: > Hi there, > > I would like some advice, not so much about how to > use R, but about software > that I need to complement R. I've rooted around in > the FAQ's and done a few > searches on this mailing list but haven't quite > found the perspective I > need. > > I am an experienced data analyst in my field (forest > ecology and ecological > monitoring) but new to R. I am a long time user of > SPSS and have gotten > pretty handy with it. However, I am frustrated with > SPSS for several > reasons: There's the cost (I'm a freelancer; I pay > for my software > myself); the Windows dependence (I use Kubuntu as > my usual OS now, and > switching back and forth is a pain); the horrible > inefficiency when I do > certain types of file manipulations; and the > inability to do the kind of > publication-quality graphs I want... I've usually > ended up using a > commercial graphing program (another source of > expense and limitation). > > I'd like to switch to using R on Kubuntu, for all > those reasons. In > addition I think the mathematical formality that R > encourages might be good > for me. > > However, reviewing the FAQ's on the R project web > site makes me realize that > I've been using SPSS as three kinds of software > really: a DBMS; a > statistical analysis package; and a graphing > package. It looks like moving > to R might involve learning three kinds of software, > not just one. I > wonder: > > 1) What open-source DBMS works most seamlessly with > R? I have seen MySQL > recommended but wonder if there are alternatives. I > sometimes need to > handle big data files. In fact a lot of my work > involves exploratory and > descriptive analyses of rather large and messy > databases from ecological > monitoring, rather than statistical tests per se. > In SPSS the data files I > have been generating have dozens of columns and > thousands of rows, often > with value and variable labels helpful for > documenting my work. > 2) For the purpose of creating publication-quality > graphs, do R users > typically need to go outside of the R system? If so, > what open-source > programs would you all recommend? > 3) Any other software I need to learn that would > make my work in R more > productive? (for example, a code editor). > > Thank you for your time, > > Martin J. Brown > Portland, Oregon > > [[alternative HTML version deleted]] > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, > reproducible code. > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
Martin Brown wrote: > [i sent this message earlier but apparently should have sent it plain > text, as follows..] > > Hi there, > > I would like some advice, not so much about how to use R, but about > software that I need to complement R. I've rooted around in the FAQ's > and done a few searches on this mailing list but haven't quite found > the perspective I need. > > I am an experienced data analyst in my field (forest ecology and > ecological monitoring) but new to R. I am a long time user of SPSS and > have gotten pretty handy with it. However, I am frustrated with SPSS > for several reasons: There's the cost (I'm a freelancer; I pay for my > software myself); the Windows dependence (I use Kubuntu as my usual > OS now, and switching back and forth is a pain); the horrible > inefficiency when I do certain types of file manipulations; and the > inability to do the kind of publication-quality graphs I want... I've > usually ended up using a commercial graphing program (another source > of expense and limitation). > > I'd like to switch to using R on Kubuntu, for all those reasons. In > addition I think the mathematical formality that R encourages might be > good for me. > > However, reviewing the FAQ's on the R project web site makes me > realize that I've been using SPSS as three kinds of software really: > a DBMS; a statistical analysis package; and a graphing package. It > looks like moving to R might involve learning three kinds of software, > not just one. I wonder: > > 1) What open-source DBMS works most seamlessly with R? I have seen > MySQL recommended but wonder if there are alternatives. I sometimes > need to handle big data files. In fact a lot of my work involves > exploratory and descriptive analyses of rather large and messy > databases from ecological monitoring, rather than statistical tests > per se. In SPSS the data files I have been generating have dozens of > columns and thousands of rows, often with value and variable labels > helpful for documenting my work. > I think you won't find much difference in the R interface between MySQL, PostgreSQL, or SQLite. The choice should be made based on the qualities of the database (and I don't know enough about the differences to give a recommendaton.) > 2) For the purpose of creating publication-quality graphs, do R users > typically need to go outside of the R system? If so, what open-source > programs would you all recommend? > R is great for this, but you might need to go outside for some specialized stuff (e.g. medical imaging). > 3) Any other software I need to learn that would make my work in R > more productive? (for example, a code editor). A lot of people are happy with ESS mode in Emacs. Duncan Murdoch __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] recommended combo of apps for new user?
[i sent this message earlier but apparently should have sent it plain text, as follows..] Hi there, I would like some advice, not so much about how to use R, but about software that I need to complement R. I've rooted around in the FAQ's and done a few searches on this mailing list but haven't quite found the perspective I need. I am an experienced data analyst in my field (forest ecology and ecological monitoring) but new to R. I am a long time user of SPSS and have gotten pretty handy with it. However, I am frustrated with SPSS for several reasons: There's the cost (I'm a freelancer; I pay for my software myself); the Windows dependence (I use Kubuntu as my usual OS now, and switching back and forth is a pain); the horrible inefficiency when I do certain types of file manipulations; and the inability to do the kind of publication-quality graphs I want... I've usually ended up using a commercial graphing program (another source of expense and limitation). I'd like to switch to using R on Kubuntu, for all those reasons. In addition I think the mathematical formality that R encourages might be good for me. However, reviewing the FAQ's on the R project web site makes me realize that I've been using SPSS as three kinds of software really: a DBMS; a statistical analysis package; and a graphing package. It looks like moving to R might involve learning three kinds of software, not just one. I wonder: 1) What open-source DBMS works most seamlessly with R? I have seen MySQL recommended but wonder if there are alternatives. I sometimes need to handle big data files. In fact a lot of my work involves exploratory and descriptive analyses of rather large and messy databases from ecological monitoring, rather than statistical tests per se. In SPSS the data files I have been generating have dozens of columns and thousands of rows, often with value and variable labels helpful for documenting my work. 2) For the purpose of creating publication-quality graphs, do R users typically need to go outside of the R system? If so, what open-source programs would you all recommend? 3) Any other software I need to learn that would make my work in R more productive? (for example, a code editor). Thank you for your time, Martin J. Brown Portland, Oregon __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] recommended combo of apps for new user?
Hi there, I would like some advice, not so much about how to use R, but about software that I need to complement R. I've rooted around in the FAQ's and done a few searches on this mailing list but haven't quite found the perspective I need. I am an experienced data analyst in my field (forest ecology and ecological monitoring) but new to R. I am a long time user of SPSS and have gotten pretty handy with it. However, I am frustrated with SPSS for several reasons: There's the cost (I'm a freelancer; I pay for my software myself); the Windows dependence (I use Kubuntu as my usual OS now, and switching back and forth is a pain); the horrible inefficiency when I do certain types of file manipulations; and the inability to do the kind of publication-quality graphs I want... I've usually ended up using a commercial graphing program (another source of expense and limitation). I'd like to switch to using R on Kubuntu, for all those reasons. In addition I think the mathematical formality that R encourages might be good for me. However, reviewing the FAQ's on the R project web site makes me realize that I've been using SPSS as three kinds of software really: a DBMS; a statistical analysis package; and a graphing package. It looks like moving to R might involve learning three kinds of software, not just one. I wonder: 1) What open-source DBMS works most seamlessly with R? I have seen MySQL recommended but wonder if there are alternatives. I sometimes need to handle big data files. In fact a lot of my work involves exploratory and descriptive analyses of rather large and messy databases from ecological monitoring, rather than statistical tests per se. In SPSS the data files I have been generating have dozens of columns and thousands of rows, often with value and variable labels helpful for documenting my work. 2) For the purpose of creating publication-quality graphs, do R users typically need to go outside of the R system? If so, what open-source programs would you all recommend? 3) Any other software I need to learn that would make my work in R more productive? (for example, a code editor). Thank you for your time, Martin J. Brown Portland, Oregon [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
