similar to: reshape2: Lost Values Between melt() and dcast()

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 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'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 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,

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"

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

Hello--I'm doing a simple crosstab using dcast: rawfreq <- dcast(nh11brfs, race3~CHCCOPD, length) with the results race3 Yes No NA 1 White non-Hispanic 446 5473 21 2 Other non-Hispanic 29 211 0 3 Hispanic 6 81 1 4 <NA> 10 83 1 How would I modify this call to exclude all missing values; that is, to obtain race3

Suppose I have a small dataframe > aa Target Eaten ID 50 TPP 0 1 51 TPP 1 2 52 TPP 3 3 53 TPP 1 4 54 TPP 2 5 50.1 GPA 9 1 51.1 GPA 11 2 52.1 GPA 8 3 53.1 GPA 8 4 54.1 GPA 10 5 And I want to reshape it into ID TPP GPA 1 1 0 9 2 2 1 11 3 3 3 8 4 4 1 8 5 5 2 10 I realise that

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 :

Hi, I'd like to get mean values for the margins of my casted data.frame. For the casting I am using dcast() from reshape2. However, when I set the margins parameter (margins=c("grand\_row")) I get following error concerning an unrecognized escape character '\_'. So what is the correct command to get the outermost margins only in reshape2? /johannes [[alternative HTML

I believe that I have a basic understanding of zoo and how to use read.zoo on a text file, What I have not seen in the zoo help files and vignettes is how to convert a data frame to a zoo matrix for irregular time series analyses. An example data frame is structured like this: str(burns.cast) 'data.frame': 256 obs. of 47 variables: $ site : Factor w/ 143 levels

Dear R communitiy, I am trying to use multiple functions for aggregation within a function call for dcast. However this seems to result in an error. Also I have not managed to make dcast() work with fun.aggregate=sd. Please find attached some example code using the ChickWeight data. Many thanks for your help! Jokel #Chick weight example names(ChickWeight) <- tolower(names(ChickWeight))

Hello, I implemented two functions reshape_long and reshape_wide (see full working example below) to reshape data frames. I created several small examples and the two functions seemed to work properly. However, using the reshape_wide function on my real data sets (about 200.000 to 300.000 rows) failed. What happens is set all values for X, Y and Z were set to 1. The structure of my real data

Hola a todos, Queria preguntaros si conoceis alguna manera para invertir la funcion dcast. Quiero transformar una matriz en un data frame de tres columnas que indiquen solo los casos donde la combinacion fila-columna sea diferente de NA. Se me habia ocurrido hacer un bucle que fuera seleccionando todos los valores para cada combinacion de fila y columna, pero el problema es que con una matriz de

I'm in the middle of my own little intellectual exercise comparing dcast() and reshape() and have successfully stumped myself. I want to melt() a data frame, then dcast() it into a new form. After doing so, I want to duplicate the process using reshape(). So far, I can do the melt and cast require(reshape2) Raw <- data.frame(site = c(1, 1, 1, 1, 2, 2, 2, 2), id =

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,

Hi, I am trying to calculated various summary statistics using the dcast function of reshape2. This works perfectly for getting the mean, sum, length, sd. But when I want to calculate the median I get an error. I tried it with and without removing NAs: my_median <- function(x) median(x, na.rm = FALSE) median_df <- dcast(patch_stats_dfm,formula=species~input+barriers,my_median) Error in

Con data.table todo puede ir muy rapido. > require(data.table) > M=matrix(c(5,NA,NA,NA,6,NA,7,NA,8),3,3) > M [,1] [,2] [,3] [1,] 5 NA 7 [2,] NA 6 NA [3,] NA NA 8 > M2=data.table(M) > M2 V1 V2 V3 1: 5 NA 7 2: NA 6 NA 3: NA NA 8 > M3=melt(M2,variable.name = "columna") > M3 columna value 1: V1 5 2: V1 NA 3: V1

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

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