similar to: Counting the Number of Letters in a row

I'm working with some data, and am trying to generate it in the following format. state city zipcode I like pizza 0 0 0 I live in Denver 0 1 0 All the fun stuff is in Alaska 1 0 0 he lives in 66062

I'm running a linear model in R using the car package. I have a variable education, which i have recoded and regrouped to my wishes. However, R seems to place each element of that variable in alphabetical order. When I am running the model, don't I need the model order from lowest to highest to make an inference that a one unit change in one variable produced a one unit change in

I have a really long functions, and at the end of the function, I am using a if statement to tag certain keywords based on whether they have certain values contained in them. However, the if statement doesn't seem to work. When I had split up the commands into various functions, it worked fine, but I'm not sure what going on now that it's combined into a single function. myfunc

I didn't learn about data tables until recently. (They're never covered in any intro R books). In any case, I'm not sure what (if any) is the difference between a data frame and a data table. Can anyone provide a brief explanation? Is one preferred over another or is it just dependent on the task at hand? Thanks, Abraham M. [[alternative HTML version deleted]]

I'm trying to develop a stacked bar plot in R with ggplot2. My data: conv = c(10, 4.76, 17.14, 25, 26.47, 37.5, 20.83, 25.53, 32.5, 16.7, 27.33) click = c(20, 42, 35, 28, 34, 48, 48, 47, 40, 30, 30) date = c("July 7", "July 8", "July 9", "July 10", "July 11", "July 12", "July 13", "July 14", "July 15",

Let's say that I'm trying to write a functions that will allow me to automate a process where I examine all possible combinations of various string groupings. Each time I run the one function, I want to include the new values to the end of a data frame. The data frame will basically be one column with a lot of rows. roots <- c("car insurance", "auto insurance")

I have the following data: prefix <- c("cheap", "budget") roots <- c("car insurance", "auto insurance") suffix <- c("quote", "quotes") prefix2 <- c("cheap", "budget") roots2 <- c("car insurance", "auto insurance") roots3 <- c("car insurance", "auto

I'm trying to run a logit model and plot the probability curve for a number of the important predictors. I'm trying to do this with the Effects package. df=data.frame(income=c(5,5,3,3,6,5), won=c(0,0,1,1,1,0), age=c(18,18,23,50,19,39), home=c(0,0,1,0,0,1)) str(df) md1 = glm(factor(won) ~ income + age + home, data=df,

So I have the following data frame and I want to know how I can remove all "NA" values from each string, and also remove all "|" values from the START of the string. So they should something like "auto|insurance" or "auto|insurance|quote" one = data.frame(keyword=c("|auto", "NA|auto|insurance|quote", "NA|auto|insurance",

I have a logit model with about 10 predictors and I am trying to plot the probability curve for the model. Y=1 = 1 / 1+e^-z where z=B0 + B1X1 + ... + BnXi If the model had only one predictor, I know to do something like below. mod1 = glm(factor(won) ~ as.numeric(bid), data=mydat, family=binomial(link="logit")) all.x <- expand.grid(won=unique(won), bid=unique(bid)) y.hat.new

I'm an R newbie and had a question about the read.xls function. I've heard that this is often not a reliable function to use for importing data. However, I have created numerous xls files which contain information about voter turnout and macroeconomic indicators in India. I'm writing a paper on the relationship between economic growth and voter turnout. This is the command I use:

I'm working on a logistic regression in R with the car package but keep getting the following error message. It's only and warning and not an error, but I'm just not sure how to resolve the issues. glm.fit: algorithm did not converge glm.fit: fitted probabilities numerically 0 or 1 occurred d1 = data.frame(mwin=c(mwin), mbid=c(mbid)) m1 = zelig(mwin ~ mbid, data=d1,

Hello folks, Here's is info on what system I'm working on. > sessionInfo() R version 2.13.0 (2011-04-13) Platform: i686-pc-linux-gnu (32-bit) I'm trying to install the XML package. However, I end up with the following error message. > install.packages("XML") .... checking for xml2-config... no Cannot find xml2-config ERROR: configuration failed for package ‘XML’ *

I'm developing a naive bayes in R. I have the following data and am trying to predict on returned (class). dat = data.frame(home=c(0,1,1,0,0), gender=c("M","M","F","M","F"), returned=c(0,0,1,1,0)) str(dat) dat$home <- as.factor(dat$home) dat$returned <- as.factor(dat$returned) library(e1071) m <- naiveBayes(returned ~ ., dat) m

I have a data frame with a column of values that I want to bucket (group) into specific levels. > str(dat)'data.frame': 3678 obs. of 39 variables: $ id : int 23 76 129 156 166 180 200 214 296 344 ... $ final_purchase_amount : Factor w/ 32 levels "\\N","1082","1109",..: 1 1 1 1 1 1 1 1 1 1 ... So I ran the following to

I'm using the subset() function in R. dat <- data.frame(one=c(6,7,8,9,10), Number=c(5,15,13,1,13)) subset(dat, Number >= 10) However, I want to find the number of all rows who meet the Number>=10 condition. I've done this in the past with something like colSums or rowSums or another similar function. But I don't remember how to get the number of elements which meet that

I'm writing a function and keep getting the following error message. myfunc <- function(lst) { lst <- list(roots = c("car insurance", "auto insurance"), roots2 = c("insurance"), prefix = c("cheap", "budget"), prefix2 = c("low cost"), suffix = c("quote", "quotes"), suffix2 = c("rate",

I'm running R in Ubuntu 10.10 and am trying to install the RODBC package. However, I get the following error message: ERROR: configuration failed for package ‘RODBC’ * removing ‘/home/amathew/R/i686-pc-linux-gnu-library/2.13/RODBC’ The downloaded packages are in ‘/tmp/RtmpekzPOQ/downloaded_packages’ Warning message: In install.packages() : installation of package 'RODBC' had

Lets say I have a linear model and I want to find the average expented value of the dependent variable. So let's assume that I'm studying the price I pay for coffee. Price = B0 + B1(weather) + B2(gender) + ... What I'm trying to find is the predicted price for every possible combination of values in the independent variables. So Expected price when: weather=1, gender=male weather=1,

I have the following variable, time, which is a character variable and it's structured as follows. > head(as.character(dat$time), 30) [1] "00:00:01" "00:00:16" "00:00:24" "00:00:25" "00:00:25" "00:00:40" "00:01:50" "00:01:54" "00:02:33" "00:02:43" "00:03:22" [12]