similar to: Log difference in a dataframe column

Newbie and trying to learn the right way of doing things in R. in this case, I just have that feeling that my convoluted line of code is way more complicated than it needs to be. Please help me in seeing the easier way. I want to do something pretty simple. I have a dataframe called x that is 6945 elements long. I'd like to create a vector rtn= log(x[2,2]/x[1,3]), then log(x[3,2]/x[2,3]),

I am calculating the mean of each column grouped by the variable 'id'. I do this using aggregate, data.table, and plyr. My aggregate results do not match the other two, and I am trying to figure out what is incorrect with my syntax. Any suggestions? Thanks. Here is the data. myData <- structure(list(var1 = c(31.59, 32.21, 31.78, 31.34, 31.61, 31.61, 30.59, 30.84, 30.98, 30.79, 30.79,

Hi [macOSX 10.4.6; R-2.3.0] I have encountered a difference in behaviour between R-2.2.1 and R-2.3.0 when performing a linear model. Transcript follows for R-2.3.0 (R-2.2.1 worked as expected). How to make R-2.3.0 perform as R-2.2.1 did? > dput(x) c(29.13, 29.88, 30.09, 29.99, 29.74, 29.64, 29.65, 29.7, 30.04, 29.89, 29.96, 29.65, 28.76, 28.41, 28.38, 29.55, 29.76, 29.75, 29.84,

Dear R-Users, Have a question about reading in some data and manipulating dates. I have a data set in excel which looks like this: Date PEG ETN HSP PTC 13/10/2004 41.92 64.75 29.86 9.27 14/10/2004 41.93 61.79 29.98 9.14 15/10/2004 41.69 62.7 30.09 9.04 18/10/2004

Hello, Using the following lines of code, I created the following graph:

Hello, Using the following lines of code, I created the following graph:

First I have a matrix called stocks1: > class(stocks1) [1] "matrix" Here are the first 5 rows of the last 4 columns: > stocks1[1:5,2:5] [,1] [,2] [,3] [,4] [1,] 80.73 31.95 25.4 25.69 [2,] 83.66 31.95 27.12 25.2 [3,] 83.27 32.93 28.74 26.29 [4,] 83.9 34.07 29.77 26.6 [5,] 82.74 35.18 30.24 27.41 Now, why can't I convert this into a dataframe?

Assuming the days of raining during half a year of all states(provinces) of a country is normally distributed (mean=?, standard deviation=?) with sigma (?) equals to 2. We now have 10 data points here: 26.64, 30.65, 31.27, 33.04, 32.56, 29.10, 28.96, 26.44, 27.76, 32.27. Try to get the 95% level of CI for ?, using parametric Bootstrap method with bootstrap size B=8000. my code - what am i doing

Dear group, Here is my df: avprix <- structure(list(DESCRIPTION = c("CORN Jul/10", "CORN May/10", "ROBUSTA COFFEE (10) Jul/10", "SOYBEANS Jul/10", "SPCL HIGH GRADE ZINC USD", "STANDARD LEAD USD"), prix = c(-1.5, -1082, 11084, 1983.5, -2464, -118), quantity = c(0, -3, 8, 2, -1, 0), fees = c(-8.64, -30.24, -26.4, -25.92, -37.5,

Hello everyone, I have a data set like this: > head( fish_transect) ID_TRANSECT ID_PROJECT DE_ZONE DE_LOCALITY DE_SECTOR MES 1 42 MB Tarragona Creixell Control I 9 2 42 MB Tarragona Creixell Control I 9 3 42 MB Tarragona Creixell Control I 9 4 42 MB Tarragona Creixell Control I 9 5 42

Hi, i have that table Thesis Day A B C 1 0 83.43 90.15 22.97 1 0 85.50 94.97 16.62 1 0 83.36 95.38 20.70 1 0 84.47 92.16 23.58 1 0 83.98 95.33 19.39 1 0 82.86 93.78 24.55 1 0 83.39 92.67 19.56 1 0 85.17 95.24 17.95 1 0 81.62 93.32 28.49 1 0 82.99 92.85 19.73 1 0 81.11 95.67 27.20 1 0 83.39 94.69 16.51 1 0 79.56 89.87 30.39 1 0 80.54 93.32 21.76 1 0 82.11 92.58 22.17 1 14 85.65 94.00 19.19 1 14

Estimada comunidad tengo un problema del que no encuentro datos que me ayuden mucho en la web. Estoy haciendo calculos por grupos con data,table. Tengo un archivo (zp.res) con tres columnas que clasifican los datos (sol, con, dia) y una columna de datos numericos (media), de la siguiente forma: sol con dia media 1: con 0 1 -22.6 2: con 0 1 -36.6 3: con 0 1 -35.6 y

I have a data-set that is structured as follows: sp wg n v.realtime v.cputime v.tcputime v.idletime v.nswtch 9 0 1 1 28.61300 28.61 28.6039 0.00000e+00 407 1563 0 1 2 15.20270 30.38 28.5981 9.80523e-01 483 3128 0 1 4 12.50930 50.00 28.6053 1.07877e+01 489 4682 0 1 6 12.10260 72.55

I have the following timeseries "tab" ===================================== > str(tab) mts [1:23, 1:2] 79.5 89.1 84.9 75.7 72.8 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "Ipex...I" "Omel...E" - attr(*, "tsp")= num [1:3] 2006 2008 12 - attr(*, "class")= chr [1:2] "mts" "ts" > tab

Dear list, here are my two data frames: av <- structure(list(DESCRIPTION = c("COFFEE C Sep/10", "COPPER Sep/10", "CORN Dec/10", "CRUDE OIL miNY Sep/10", "GOLD Aug/10", "HENRY HUB NATURAL GAS Sep/10", "PALLADIUM Sep/10", "SILVER Sep/10", "SOYBEANS Nov/10", "SPCL HIGH GRADE ZINC USD", "SUGAR

Dear all i use R only a few days and don't understand the difference between fivenum(x) und summary(x). > x [1] 20.77 22.56 22.71 22.99 26.39 27.08 27.32 27.33 27.57 27.81 28.69 29.36 [13] 30.25 31.89 32.88 33.23 33.28 33.40 33.52 33.83 33.95 34.82 > fivenum(x) [1] 20.770 27.080 29.025 33.280 34.820 > summary(x) Min. 1st Qu. Median Mean 3rd Qu. Max. 20.77 27.14

I'm trying to extend a logical volume and I'm doing as follow: 1- Run `fdisk -l` command and this is the output: Disk /dev/sda: 85.9 GB, 85899345920 bytes 255 heads, 63 sectors/track, 10443 cylinders Units = cylinders of 16065 * 512 = 8225280 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier:

Greetings all, Ran into a strange problem with the krige function from geoR. The problem that I am having is that while the krige function seems to work well, the resulting predicted values are all NAs. Given the size of the datasets I am working with can't attach it, but I can provide snippets of the datasets. > casedata station year month day obs mpe bias type

Hello, I want to fit a Gompertz model for tree diameter growth that depends on a 4 levels edaphic factor (?Drain?) and I don?t manage to introduce the factor variable in the formula. Dinc is the annual diameter increment and D is the Diameter. >treestab > Dinc D Drain [1,] 0.03 26.10 2 [2,] 0.04 13.05 1 [3,] 0.00 24.83 1 [4,] 0.00 15.92 4

Hello everyone, I have a data set like this: > head( fish_transect) ID_TRANSECT ID_PROJECT DE_ZONE DE_LOCALITY DE_SECTOR MES 1 42 MB Tarragona Creixell Control I 9 2 42 MB Tarragona Creixell Control I 9 3 42 MB Tarragona Creixell Control I 9 4 42 MB Tarragona Creixell Control I 9 5 42