similar to: Sequence generation in a table

Dear R helpers, xx = data.frame(country = c("USA", "UK", "Canada"), x = c(10, 50, 20), y = c(40, 80, 35), z = c(70, 62, 10)) > xx        country      x     y    z 1      USA        10    40  70 2      UK          50   80   62 3     Canada    20   35   10 I need to arrange this as a new data.frame as follows - country       type     values USA           

Dear R helpers Suppose I have a vector as vect1 = as.character(c("ABC", "XYZ", "LMN", "DEF")) > vect1 [1] "ABC" "XYZ" "LMN" "DEF" I want to reverse the order of this vector as vect2 = c("DEF", "LMN", "XYZ", "ABC") Kindly guide Regards Vincy [[alternative HTML

Dear R helpers, I have one basic doubt about the value of pi. In school, we have learned that pi = 22/7 (which is = 3.142857). However, if I type pi in R, I get pi = 3.141593. So which value of pi should be considered? Regards Vincy [[alternative HTML version deleted]]

Dear R helpers Wish you all a very Happy and Prosperous New Year 2011. I have following query. country = c("US", "France", "UK", "NewZealand", "Germany", "Austria", "Italy", "Canada") Through some other R process, the result.csv file is generated as result.csv      var1   var2  var3  var4    var5    var6   var7  

Dear R helpers I have a data which gives Month-wise and Rating-wise Rates. So the input file is something like month           rating           rate January        AAA             9.04 February      AAA             9.07 .......................................... .......................................... Decemeber     AAA            8.97  January           BBB           11.15 February        

Dear R helpers I have a dataframe as df = data.frame(x = c(1, 14, 3, 21, 11), y = c(102, 500, 40, 101, 189)) > df    x   y 1  1 102 2 14 500 3  3  40 4 21 101 5 11 189 # Actually I am having dataframe having multiple columns. I am just giving an example. I need to subtract all the rows of df by the first row of df i.e. I need to subtract each element of 'x' column by 1. Likewise I

Dear R list, I have one very elementary question regrading correlation between two variables. x = c(44,46,46,47,45,43,45,44) y = c(44,43,41,41,46,48,44,43) > cov(x, y) [1] -2.428571 However, if I try to calculate the covariance using the formula as covariance = sum((x-mean(x))*(y-mean(y)))/8       # no of of paired obs. = 8 or     covariance = sum(x*y)/8-(mean(x)*mean(y)) gives

Dear R list As suggested by Prof Brian Ripley, I have tried to read acf literature. The main problem is I am not the statistician and hence have some problem in understanding the concepts immediately. I came across one literature (http://www.stat.nus.edu.sg/~staxyc/REG32.pdf) on auto-correlation giving the methodology. As per that literature, the auto-correlation is arrived at as per following.

Hi, I have one basic doubt. Suppose X ~ N(50,10). I need to calculate Probability X = 50. dnorm(50, 50, 10) gives me [1] 0.03989423 My understanding is (which is bit statistical or may be mathematical) on a continuous scale, Probability of the type P(X = .....) are nothing but 1/Infinity i.e. = 0. So as per my understanding P(X = 50) should be 0, but even excel also gives 0.03989422. Obviously

Dear R helpers, (At the outset I sincerely apologize if I have not put forward my following query properly, though I have tried to do so.) Following is a curtailed part of my R - code where I am trying to generate say 100 random no.s for each of the products under consideration. library(plyr) n = 100 my_code = function(product, output_avg, output_stdev)     { BUR_mc = rnorm(n, output_avg,

Dear R helpers Suppose I have a vector as vect_1 = c("AAA", "AA", "A", "BBB", "BB", "B", "CCC") vect_1_id = c(1:length(vect_1)) Through some process I obtain vect_2_id = c(2, 3, 7), then I need a new vector say vect_2 which will give me vect2 = ("AA", "A", "CCC")  i.e. I need the subset of

Dear R helpers, I have recently installed R version 2.15.0 I just wanted to calculate mean(16, 18) Surprisingly I got answer as > mean(16, 18) [1] 16 > mean(18, 16) [1] 18 > mean(14, 11, 17, 9, 5, 18) [1] 14 So instead of calculating simple Arithmetic average, mean command is generating first element as average. I restarted the machine, changed the machine, but still the

Dear R helpers, Suppose I have stock returns data of say 1500 companies each for say last 4 years. Thus I have a matrix of dimension say 1000 * 1500 i.e. 1500 columns representing companies and 1000 rows of their returns. I need to find the correlation matrix of these 1500 companies. So I can find out the correlation as cor(returns) and expect to get 1500 * 1500 matrix. However, the process

Dear 'HTH' R friends I have a small dataframe as given below. I need to sort this database based on date in a decending order. I am not sure whether I have defined the date column in a proper format. mydat<-data.frame(date = (c("1/31/2010", "2/28/2010", "3/31/2010", "4/30/2010", "5/31/2010", "6/30/2010",

Dear R helpers Suppose I have a data frame as given below mydat = data.frame(x = c(1,1,1, 2, 2, 2, 2, 2, 5, 5, 6), y = c(10, 10, 10, 8, 8, 8, 7, 7, 2, 2, 4)) mydat         x     y 1      1     10 2      1     10 3      1     10 4      2       8 5      2       8 6      2       8 7      2       7 8      2       7 9      5       2 10    5       2 11    6       4 unique(mydat$x) will give me 1,

Dear R helpers, I have one trivial problem while writing an output file in csv format. I have two dataframes say df1 and df2 which I am reading from two different csv files. df1 has column names as date, r1, r2, r3 while the dataframe df2 has column names as date, 1w, 2w. (the dates in both the date frames are identical also no of elements in each column are equal say = 10). I merge these

Dear R helpers, I am using Beta distribution to generate the random no.s (recovery rates in my example). However, each time I need to save these random no.s in a csv format. To distinguish different csv files, one way I thought was use of Sys.time in the file name. My code is as follows - # My code rr = rbeta(25, 6.14, 8.12) lgd = 1 - mean(rr) write.csv(data.frame(recovery_rates = rr), file =

Dear R helpers, I have a data.frame as given below - dat1 = data.frame(date = as.Date(c("3/30/12","3/29/12","3/28/12","3/27/12","3/26/12", "3/23/12","3/22/12","3/21/12","3/20/12", "3/30/12","3/29/12","3/28/12","3/27/12",

Dear R helpers Suppose I have a data.frame as given below - my_dat = data.frame(class = c("XYZ", "XYZ", "XYZ", "XYZ", "XYZ","ABC", "ABC", "ABC", "ABC", "ABC" ),  var1 = c(20, 14, 89, 81, 17, 44, 36, 41, 11, 36), var2 = c(1001, 250, 456, 740, 380, 641, 111, 209, 830, 920)) > my_dat    class

Dear R helpers, I am not a statistician and right now struggling with Richards curve. Wikipedia says (http://en.wikipedia.org/wiki/Generalised_logistic_function) The "generalized logistic curve or function", also known as Richard's curve is a widely-used and flexible sigmoid function for growth modelling, extending the well-known logistic curve. Now I am confused and will like to