similar to: Creating ZOO Matrix from Data Frame

Thanks to David's help I subset my large data set and produced a smaller one for a single stream and 7 factors of interest. The structure of this data frame is: str(burns.tds.anal) 'data.frame': 718 obs. of 4 variables: $ site : Factor w/ 143 levels "BC-0.5","BC-1",..: 1 1 4 6 4 4 4 5 5 5 $ sampdate: Date, format: "1996-06-02"

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 have measured values for 47 chemicals in a stream. After processing the original data frame through reshape2, the recast data frame has this structure: 'data.frame': 256 obs. of 47 variables: $ site : Factor w/ 143 levels "BC-0.5","BC-1",..: 1 1 1 2 2 2 2 2 2 2 ... $ sampdate : Date, format: "1996-04-19" "1996-05-21" ... $ Acid :

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 read ?zoo but am not sure how to relate the parameters (x, order.by, frequency, and style) to my data.frame. The structure of the data.frame is '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/

I have a data frame with 1 factor, one date, and 37 numeric values: str(waterchem) 'data.frame': 3525 obs. of 39 variables: site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1 1 1 1 ... $ sampdate : Date, format: "2007-12-12" "2008-03-15" ... $ CO3 : num 1 1 6.7 1 1 1 1 1 1 1 ... $ HCO3 : num 231 228 118 246

A data frame has one factor, one date, and one numeric column. When I plot these using the default pch of the open circle (first attachment), xyplot(TDS ~ sampdate | she.s, data = sheep.cast, main = 'TDS in Sheep Creek', ylab = 'Concentration (mg/L)', xlab = 'Time') I see the higher concentration points toward the right on several panels. But, when I change to using a

The data set (called 'chemdata') has 6 columns (4 factors, 1 date, 1 numeric) and I need to create subsets for each of one of the factors ('stream'). This has worked flawlessly for all but two streams which were created yesterday. The command I use to create the subsets is like this: > rnchH <- subset(chemdata, stream == 'RanchSpgsH', select = c(site, sampdate,

I would appreciate pointers on what I should read to understand this output: summary(lm(TDS ~ Cond + Ca + Cl + Mg + Na + SO4)) Call: lm(formula = TDS ~ Cond + Ca + Cl + Mg + Na + SO4) Residuals: ALL 1 residuals are 0: no residual degrees of freedom! Coefficients: (6 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 125 NA

All but one of the summaries of multiple linear regressions in this analysis set present the residuals by min, 1Q, median, 3Q, and max. Example: lm(formula = TDS ~ Cond + Ca + Cl + Mg + Na + SO4, data = snow.cast) Residuals: Min 1Q Median 3Q Max -277.351 -32.551 -2.621 40.812 245.272 The one that doesn't has only a small number of rows (23) and presents the

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

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

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

The sample data sets that come with the NADA package are limited to one or two variables and a censored measurement indicator column. I try to mimic examples using my data but keep missing the target. My water chemistry data is available in two formats: long (as seen in a database table) and wide (as seen in a spreadsheet). The two structures are: str(chem) 'data.frame': 65349 obs. of

Rich, The documentation for cenboxplot states that the second argument must be logical and not integer. the function cenboxplot substitutes synthetic values for censored values using ros, hence the error message from the ros method. I also do not understand how you expect group = 'SO4' to work. It is not clear that the function will replicate 'SO4' to make a single group.

I want to create individual data.frames for each of the 8 param factors in chemdata. The syntax I tried (based on Teetor's book, page 132) and R's response are: > ars <- subset(chemdata, select=c(site,sampdate,param,quant), subset=(param = "As")) Error in subset.data.frame(chemdata, select = c(site, sampdate, param, : 'subset' must evaluate to logical

Before reading water chemistry into a data frame I removed all missing data. Yet when I try to run cenros() to summarize a specific chemical I get an error that I do not understand: with( subset(chem, param=='Ag'), cenros(quant,ceneq1) ) Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : NA/NaN/Inf in 'y' I would like to learn what I did incorrectly

I've gone over the data and do not see my error; the dput() output of the data frame and the pdf output of cenboxplot() are attached. The command used: cenboxplot(sb.t$quant, sb.t$ceneq1, range=1.5, main='Total Recoverable Antimony', xlab='Pre-Mining Era', ylab='Concentration (log mg/L)') (on a single line in emacs). The RL on the plot is drawn at 0.01 rather

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",..:

I've tried various commands. ?plot, Teetor's book, "R Cookbook", and Mittal's book, "R Graphs Cookbook" without seeing how to write the command to create scatterplots from my data.frame. The structure is: > str(chemdata) 'data.frame': 14886 obs. of 4 variables: $ site : Factor w/ 148 levels "BC-0.5","BC-1",..: 104 145 126 115