similar to: Overplotting: plot() invocation looks ugly ... suggestions?

Hello all! I have a problem with ggplot2 library. I want to do an heat map and the y variables are the year months. If I use the following code, he y values are in alphabetical order, but I want it in month order. The code is: library(reshape) library(ggplot2) library(scales) p <- ggplot(data.m, aes(variable, Month)) + geom_tile(aes(fill = value),

Hi, again i am stuck in my presentation, and i have never learn R before in my life but need this to be done, so please help me out for a favour: http://www.nabble.com/file/p20333155/kew.dat kew.dat run this in R and these comes up: Month Year Rain 1 Jan 1900 74.400000 2 Feb 1900 80.500000 3 Mar 1900 23.600000 4 Apr 1900 23.600000 5 May 1900 25.100000 6

Dear R users, [in case the format of email is changed or you dont finf it easy to understand, i have attached a text file of my question] i have the data in the following format and i want to convert it in the format given at the end. Ta ans Sa are the names of certain cities. there are 69 cities in my data. column 1 is representing station name (i am writing the data of only two cities for

Dear Rui and UseRs,[a text file has also been attached, in case the format of my email is difficult to get]I am extremely sorry that I am bothering you once again, but I?ll have to get to the bottom of it. The following command sp <- lapply(split(agg, agg$st), function(x) x[order(x$year, x$month), ]) gave me an output with monthly mean of population(as under). i am not able to apply

I am using windows XP with R 2.8.1 I am generating a lattice plot of annual rain patterns using the following function: > xyplot(rain.stats$min+ rain.stats$max + rain.stats$ave ~ rain.stats$month |rain.stats$year, lty = 1, data = rain.stats, type = c("l","l", "l"), col = c("red", "blue", "green"), distribute.type =

Hi all: I'm struggling with getting my data re-formatted using functions in reshape/reshape2 to get from: 1957 0.862500000 1958 0.750000000 1959 0.300000000 1960 0.287500000 1963 0.675000000 1964 0.937500000 1965 0.025000000 1966 0.387500000 1969 0.087500000 1970 0.275000000 1973 0.500000000 1974 0.362500000 1976 0.925000000 1978 0.712500000 1979 0.337500000 1980 0.700000000 1981 0.425000000

Dear fellow R users, I would like to draw a "sunflowerplot" because I have data (decade by month) that plots multiple times on the same x-y co-ordinates. Further I would like to colour each of the points/sunflower leaves on the plot according to the group they belong to (i.e. which type of event each represents within that decade and month). I thought that this would be relatively

This does not use reshape/reshape2, but it is pretty straightforward. Assuming X is your example data: > Y <- split(X[, 2], X[, 1]) > vals <- sapply(Y, length) > pad <- max(vals) - vals > Y2 <- lapply(seq_along(Y), function(x) c(Y[[x]], rep(NA, pad[x]))) > names(Y2) <- names(Y) > X2 <- do.call(cbind, Y2) > X2[, 1:6] 1957 1958 1959

The reason it doesn't work easily with reshape/reshape2 is that the order of the rows is not determined. Your answer could be 1957 1958 ... 1985 1986 0.8625000 0.7500000 ... 0.7307692 0.23750000 0.0733945 0.6435644 ... NA 0.05769231 0.5096154 NA ... NA 0.65137615 or 1957 1958 ... 1985 1986 0.0733945 0.6435644 ... NA

Dear R Helpers: I have a data set where the unit of observation is country-year. I would like to generate a new data set based on some inclusionary (exclusionary) criteria. Here is an example of the type of data that I have. df<-data.frame(cbind("country"=c(rep("Angola", 9), rep("Burundi", 7), rep("Chad", 13)), "year"=c(1975:1983, 1989:1995,

Hi Tom, Or perhaps: #assume the data frame is named "tadf" library(prettyR) stretch_df(tadf,1,2) Jim On Thu, Jul 6, 2017 at 6:50 AM, Ista Zahn <istazahn at gmail.com> wrote: > The reason it doesn't work easily with reshape/reshape2 is that the > order of the rows is not determined. Your answer could be > > 1957 1958 ... 1985 1986 >

[Copied to R-devel for information] This applies to all versions of R I have: 0.62.2, 0.62.3, 0.63. Great care seems needed with glms with offsets, as many things seem wrong. Consider the following: > data(freeny) > freeny.glm <- glm(y ~ offset(lag.quarterly.revenue) + price.index + income.level + market.potential, data=freeny, subset=1:30) > predict(freeny.glm) Qtr1

Hello all! I have a problem with R. I try to merge data like this: structure(c(2.1785, 1.868, 2.1855, 2.5175, 2.025, 2.435, 1.809, 1.628, 1.327, 1.3485, 1.4335, 2.052, 2.2465, 2.151, 1.7945, 1.79, 1.6055, 1.616, 1.633, 1.665, 2.002, 2.152, 1.736, 1.7985, 1.9155, 1.7135, 1.548, 1.568, 1.713, 2.079, 1.875, 2.12, 2.072, 1.906, 1.4645, 1.3025, 1.407, 1.5445, 1.437, 1.463, 1.5235, 1.609, 1.738, 1.478,

Dear R users, I try to write an rcode for a paranetric weibull model with unobserved heterogeneity. The data I have are giuven below. ( The data comes from Keiding and Klein artricle published in the Statistics in Medicine 1996) . While the simple weibull model runs perfectly ( I get -2*loglikelihood 1093,905), the weibull frailty model does not run well. The code I write is :

Hi all, I have been chipping away at a problem I encountered in calculating rates per year from a moderately large data file (46412 rows). When I ran the following command, I got obviously wrong output: interval<- c(NA,as.numeric(diff( strptime(mkdf$MEAS_DATE,"%d/%m/%Y")))/365.25) The values in MEAS_DATE looked like this: mkdf$MEAS_DATE[1:10] [1] 1/5/1962 1/5/1963

Hello all! I have a problem to extract values greater that for example 1820. I try this code: x[x[,1]>1820,]->x1 Please help me! Thank you! The data structure is: structure(c(2.576, 1.728, 3.434, 2.187, 1.928, 1.886, 1.2425, 1.23, 1.075, 1.1785, 1.186, 1.165, 1.732, 1.517, 1.4095, 1.074, 1.618, 1.677, 1.845, 1.594, 1.6655, 1.1605, 1.425, 1.099, 1.007, 1.1795, 1.3855, 1.4065, 1.138, 1.514,

Hello all! I have a problem to group my data (years) in 10 years classes. For example for year year decade 1598 1590-1600 1599 1590-1600 1600 1590-1600 1601 1600-1610 --- my is like this> [1] 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 [16] 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 [31] 1628 1629 1630 1631 1632 1633

Hi all, I'm looking at a large data set, and I'm interested in removing rows where only one variable is duplicated. Here's an example: > presidents Qtr1 Qtr2 Qtr3 Qtr4 1945 NA 87 82 75 1946 63 50 43 32 1947 35 60 54 55 1948 36 39 NA NA 1949 69 57 57 51 1950 45 37 46 39 1951 36 24 32 23 1952 25 32 NA 32 1953 59

Hi everybody, If I've a data frame like this: dataframe a X0 X2 X4 X6 X8 X10 X12 X14 X16 1957 0 0 0 0 0 0 0 0 0 1958 0 0 0 0 0 0 0 0 0 1959 831 0 0 0 0 0 0 0 0 1960 544 282 0 0 0 0 0 0 0 1961 446 365 0 0 0 0 0 0 0 1962 442 473 0 0 0 0 0 0 0 1963 595 468 0 0 0 0 0 0 0 1964

Hello all! I have a problem with my data in R. When I want to plot the following data, I have a problem with y scale. The maximum value is cc. 10 degrees and in R is about 100. I use this code: fasy<-read.table("gridd1.txt",sep="\t",dec=",",header=T,row.names=1) # here are the years: x <- as.numeric(rownames(fasy)) # extract a series that you want to plot: y