# Any gaps will be filled by "NA" values. # If v.names are not specified, all variables apart from idvar and timevar are assumed to vary, and are spread wide. VALUES of CONC are spread "wide" ( v.names). Columns are labelled with TIME ( timevar) Keep SUBJECT as the identifying variable, one per row ( idvar) We want to group them together by some variable that identifies an individual (group of observations). Indometh # one of the built-in R datasets. But let's glance at long-to-wide transformation: There are several methods reshape is powerful.
one row per subject multiple observations/column per subject) and "long" format (one observation per row). Often, you need to transform data between "wide" format (e.g. In the R Commander, you can click the Data set button to select a data set, and then click the Edit data set button.įor more advanced data manipulation in R Commander, explore the Data menu, particularly the Data / Active data set and Data / Manage variables in active data set menus. Y <- edit(x) fix(x) # equivalent to x <- edit(x) X <- scan(" # the same, but from a URL (live)Įditing a variable, matrix, or data frame: X <- scan(filename) # do the same but reading from a file on disk X <- scan() # type in numbers, separated by spaces or newlines hit Enter twice to finish Typing stuff in note also that filenames and URLs are often interchangeable: Rm(x) # removes object "x" (if you know UNIX, this will be familiar) Other important object manipulation functions: ls() # list all objects (if you know UNIX, this will be familiar) # Another way, which has no residual effects: Search() # shows the current search path (will now include my.dataset)ĭetach(my.dataset) # when we've finished with it # By the way, get used to the R convention: my.dataset is just a variable name the dot doesn't mean anything special. # (otherwise a new variable called var is created that simply "overlies" the dataset. # Note that to change variables in the dataset, you still need to assign to dataset$var Making a data set visible on the main search path: attach(my.dataset) # we now don't need to use my.dataset$X, my.dataset$Y we can just use X and Y directly
It's easy to sort data frames and to create new variables based on existing ones. there are lots of things you can do with this command see ?subset. Terms and conditions apply.See website for details.X 3 # will make temp equal to the logical vector c(FALSE, FALSE, FALSE, TRUE, TRUE) by performing comparisons on each element of v ** For UK companies only, upon eligibility. * SEK cards and accounts currently available for EU-based companies only. Juni is made for ecommerce businesses, marketing and ad agencies and media buyers. *Watch your business grow over time as you would with your favorite stock ticker *Recieve personal support with dedicated account managers * Improve cashflow with flexible credit limits from £10k to £2M** *Pay and get paid in the right currency and avoid heavy FX fees *Receive 2% cashback for your first 30 days, up to 1% thereafter *Create cards and accounts in USD, EUR, GBP and SEK* Get centralised overview of all your bank accounts, networks and payment services With Juni, you can now track your entire business in one place on our financial management platform made for ecommerce. You already track your Return On Ad Spend.