similar to: Missing Vignettes for reshape2

I need to understand how and why dcast() adds NAs to a data frame that contained no missing values. The database table of chemical concentrations has all missing values removed because they cannot contribute to data analyses. The structure of the R data frame of these data have no NA values, and neither does the data frame resulting from applying the reshape2 melt() function to it. However,

I just upgraded from 2.14 to 2.15 and have run into an issue upgrading libraries that I've not had in previous version upgrades. For example, trying to install reshape2 for 2.15 throws errors and I don't see what to change to over come the problem: > install.packages("reshape2") Installing package(s) into ?/home/rshepard/R/i486-slackware-linux-gnu-library/2.15? (as ?lib? is

I have a reshaped data frame with value column headings concatenated from two column headings in the melted data frame. I want to change all 56 headings in a single command, but 'names' allows me to change only one at a time. In Hadley's 2007 article on reshape in the Journal of Statistical Software he mentions a 'rename' function, but I cannot find that. Is there a way to

I have water chemistry data with censored values (i.e., those less than reporting levels) in a data frame with a narrow (i.e., database table) format. The structure is: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "2007-12-12" "2007-12-12" ... $ preeq0 : logi TRUE TRUE TRUE TRUE TRUE

This is my first excursion into using reshape2 and I want to ensure that the melt() function call is syntactically correct. The unmodifed data frame is organized this way: head(tds.anal) site sampdate param quant 1 UDS-O 2006-12-06 TDS 10800 4 STC-FS 1996-06-14 Cond 280 7 UDS-O 2007-10-04 Mg 1620 9 UDS-O 2007-10-04 SO4 7580 19 JCM-10B 2007-06-21 Ca 79 20

I've successfully reformatted data frames from long to wide with reshape2, but this time I'm getting errors that I want to understand and resolve. Here's the data frame structure and the results of the melt() and dcast() functions: str(waterchem) 'data.frame': 128412 obs. of 8 variables: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1

Working with 5 subset streams from my source data frame, three of them successfully call dcast(), but two fail: jerritt.cast <- dcast(jerritt.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length and winters.cast <- dcast(winters.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length Yet both data frames have the values in their

I have a data frame called chemdata with this structure: > str(chemdata) 'data.frame': 14886 obs. of 4 variables: $ site : Factor w/ 148 levels "BC-0.5","BC-1",..: 104 145 126 115 114 128 124 2 3 3 ... $ sampdate: Date, format: "1996-12-27" "1996-08-22" ... $ param : Factor w/ 8 levels "As","Ca","Cl",..:

One of many scripts to produce 4 lattice plots on one page keeps throwing an error. I've tried manipulating the file to eliminate the error, but have not been able to do so. The error is: > source('bicarb.R') Error in source("bicarb.R") : bicarb.R:15:1: unexpected symbol 14: 15: hco33 ^ The 'h' is in column 0 so the caret would be column -1, but it's

The bio.infer package contains a data frame /usr/lib/R/library/bio.infer/data/itis.ttable.rda that needs to be modified. After loading the bio.infer package and attaching the data frame with the data() function, I wrote the data frame to a text file. After adding another row to the data frame I applied read.table() to create a data frame, but it's in my pwd, not the R library data

On Mon, 8 Apr 2024, Ivan Krylov wrote: > Questions about building R do get asked here and R-devel. Since you're > compiling a released version of R and we don't have an R-SIG-Slackware > mailing list, R-help sounds like the right place. Ivan, Okay: > What are the last lines of the build log, containing the error message? If > it's a LaTeX error, it may be that you

I've looked at the lattice book and the 'R Graphics Cookbook' without seeing how to change the labels along the x axis for groups in a box plot, specifically cenbox(). The attached example has a main and axes labels with default group labels. Please point me to a reference on how I can change 'FALSE' and 'TRUE' to something more easily understood by viewers. TIA,

Hello R user, I have a data set from a longitudinal study ( sample below) where subjects are followed over time. Second column (status) contains info about if subject is dead or still in the study and third column is time measured in the week. Here is what I need: if status is not dead or unknown take the last week, if status is dead or unknown I need to have corresponding week. Desired resulst:

Hi Albrecht, I am forwarding your reply to the full group. It's been a while since I did this and I don't remember the details. Maybe someone else can comment. (I am a bit busy at the moment.) If no one supplies the information in a few days I will try to take a look. In the meantime you can start your reading on-line. :-) Regards, Eric Dear Eric, I downloaded the material from

One set of data has censored (less-than detection limits) water chemistry concentrations for 80-100% of all observations. My initial trial-and-error attempts to apply the cenboxplot() method suggests that it has an upper limit to the percentage of censored observations. I do not see this limit in Dennis Helsel's second edition. Has anyone experience plotting censored data and can provide

I read in ?na.omit that it returns the object with incomplete cases removed. I interpret this to mean that any zoo object row where any column shows 'NA' will be removed from the data set. That's not what I need, since the 'NA' represents information in my context. However, what I would like to do is eliminate the rows where every column is 'NA'. When I aggregate

With multiple panels in a lattice trellis plot the sequence is, for example, 1, 10, 11, 12, 2, 3, 4. I want the sequence to be 1, 2, 3, 4, 10, 11, 12. Reading ?strip.default and the appropriate section in the Lattice book I'm not seeing how to specify the 'human' numeric order rather than the computer numeric order. A pointer will be appreciated. TIA, Rich

Because of regulatory requirement changes over several decades and weather conditions preventing site access the variables in my data set have different lengths. I'd like guidance on how to perform linear regressions and other models with these variables. For example, there are 2206 rows for the parameter "TDS" but only 1191 rows for the parameter "Cond." Such

I don't see what's missing in my statements to add rows to a data frame and someone else will probably see what needs to be added to the statements. The data frame has this structure (without any data): $ PHYLUM : chr $ SUBPHYLUM : chr $ SUPERCLASS : chr $ CLASS : chr $ SUBCLASS : chr $ INFRACLASS : chr $ SUPERORDER : chr $ ORDER : chr $ SUBORDER :

Data frame has this structure: 'data.frame': 11169 obs. of 4 variables: $ stream : Factor w/ 37 levels "Burns","CIL",..: 1 1 1 1 1 1 1 1 1 1 ... $ sampdate: Date, format: "1987-07-23" "1987-09-17" ... $ param : Factor w/ 8 levels "As","Ca","Cl",..: 1 1 1 1 1 1 1 1 1 1 ... $ quant : num 0.01 0.01 0.01 0.01