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Hi, I have a data frame with 3 columns: ID, year and score. How can I select for each unique ID, the year that has the max score? For example, for data frame ID, year, score tom, 1995, 88 rick, 1994, 90 mary, 2000, 97 tom, 1998, 60 mary, 1998,100 I shall have ID, year, score tom, 1995, 88 rick, 1994, 90 mary, 1998,100 Thanks, Richard [[alternative HTML version deleted]]

Hi, I don't know what I am doing wrong to the toupper does not seem working in sub + regex. The following returns 's' not the upper class 'S' as I expect: sub("q_([a-z])[a-zA-Z]*",toupper('\\1'),"q_sviRaw") Can someone tell me where I did wrong? Thanks, Richard [[alternative HTML version deleted]]

Hi, R function aggregate can only take summary stats functions, can I aggregate text columns? For example, for the dataframe below, > a <- rbind(data.frame(id=1, name='Tom', hobby='fishing'),data.frame(id=1, name='Tom', hobby='reading'),data.frame(id=2, name='Mary', hobby='reading'),data.frame(id=3, name='John',

Hi, is there an R function like sql's TOP key word? I have a dataframe that has 3 columns: company, person, salary How do I get top 5 highest paid person for each company, and if I have fewer than 5 people for a company, just return all of them? Thanks, Richard [[alternative HTML version deleted]]

Hi, This is not exactly an R question but I am trying to use gsub to replace a string that contains 5-9 alpha-numeric characters, at least one of which is a number. Is there a good way to write it in a one line regex? Thanks, Richard

Hi, sorry if it is a too stupid question, but how do I a string search in R: I have a dataframe A with A$test like: test1 bcdtestblabla2.1bla cdtestblablabla3.88blabla and I want to search for string that start with 'dtest' and ends with number and return the location of that substring and the number, so the end result would be: NA NA 3 2.1 2 3.88 I find grep can

Hi, I am trying to aggregate max a Date type column but have weird result, how do I fix this? > a <- rbind( + data.frame(name='Tom', payday=as.Date('1999-01-01')), + data.frame(name='Tom', payday=as.Date('2000-01-01')), + data.frame(name='Pete', payday=as.Date('1998-01-01')), + data.frame(name='Pete',

Hi, I have a correlation matrix of about 3000 items, i.e., a 3000*3000 matrix. For each of the 3000 items, I want to get the top 50 items that have the highest correlation with it (excluding itself) and generate a data frame with 3 columns like ("ID", "ID2", "cor"), where ID is those 3000 items each repeat 50 times, and ID2 is the top 50 correlated items with ID,

...s: OP2003Seppos.AICnonsp-OP2003Seppos.AICsp #[1] -4 (OP2003Seppos.lf0.p<-exp(OP2003Seppos.lf0$beta)/(1+exp(OP2003Seppos.lf0$beta ))) #P non spatial #[1] 0.9717596 (OP2003Seppos.lf.p<-exp(OP2003Seppos.lf$beta)/(1+exp(OP2003Seppos.lf$beta))) #P spatial #[1] 0.9717596 It must what have an important influence at kriging, because it shows as following: OP2003Sepposbin.krig<-glsm.krige(OP2003Seppos.tune,loc=OP2003Seppospro.pred. grid,bor=OP2003Sepposbor) #glsm.krige: Prediction for a generalised linear spatial model #There are 50 or mode advices (use warnings() to see them) #> warnings(...

Hello, can someone help? How come > gsub("\bINDS\b","INDUSTRIES","ADVANCED ENERGY INDS") [1] "ADVANCED ENERGY INDS" not ADVANCED ENERGY INDUSTRIES Thanks. Richard [[alternative HTML version deleted]]

Hi, I know I can do this with a for loop with strsplit and grep, but is there more efficient way? Given a data dataframe (input) and a category column (lst), > input item loc 1 item 1.1: earnings <sep> item 1.2: w2 <sep> shelf 1 2 item 1.3: deductions drawer 1 3 item 1.1:

Hi, is there a good way (instead of a time-consuming for loop) to transfer a key/value pair dataframe to a dataframe with key as column and value as row? For example, I have a dataframe with three columns: id, code, value: id,code,value 1,hi,10.3 1,lo,5.2 2,hi,19.4 3,hi,20 3,lo,12 4,lo,5.8 I want to get a dataframe like this: id,hi,lo 1,10.3,5.2 2,19.4,NA 3,20,12 4,NA,5.8 Thank you,