Hi,
You could use: creek <- read.csv("creek.csv",sep="\t") colnames(creek) <- c("date","flow") creek$date <- as.Date(creek$date, "%m/%d/%Y") creek1 <- within(creek, year <- format(date, '%Y')) library(data.table) creek2<- data.table(creek1) creek2[,list(MEAN=.Internal(mean(flow)),MEDIAN=median(flow),MAX=max(flow),MIN=min(flow)),by=list(year)] # year MEAN MEDIAN MAX MIN #1: 1999 0.6365604 0.47695 7.256 0.3187 #2: 2000 0.2819057 0.20810 2.380 0.1370 #3: 2001 0.2950348 0.22260 2.922 0.1769 #4: 2002 0.5345666 0.21190 14.390 0.1279 #5: 2003 1.0351742 0.71730 10.150 0.3492 #6: 2004 0.9691180 0.65240 11.710 0.4178 #7: 2005 1.2338066 0.72790 17.720 0.4722 #8: 2006 0.5458652 0.42820 3.351 0.2651 #9: 2007 0.6331271 0.40410 9.629 0.2784 #10: 2008 0.8792396 0.64770 4.596 0.4131 #11: 2009 0.8465300 0.59450 6.383 0.3877 A.K. ----- Original Message ----- From: Janesh Devkota <janesh.devk...@gmail.com> To: r-help@r-project.org Cc: Sent: Friday, February 1, 2013 2:32 AM Subject: [R] Summary of data for each year Hello All, I have a data with two columns. In one column it is date and in another column it is flow data. I was able to read the data as date and flow data. I used the following code: creek <- read.csv("creek.csv") library(ggplot2) creek[1:10,] colnames(creek) <- c("date","flow") creek$date <- as.Date(creek$date, "%m/%d/%Y") The link to my data is https://www.dropbox.com/s/eqpena3nk82x67e/creek.csv Now, I want to find the summary of each year. I want to especially know mean, median, maximum etc. Thanks. Janesh [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.