Hello,
One possibility is:
> creek <- read.csv("creek.csv")
> colnames(creek) <- c("date","flow")
> creek$date <- as.Date(creek$date, "%m/%d/%Y")
> creek <- within(creek, year <- format(date, '%Y'))
> with(creek, aggregate(flow, by=list(year=year), summary))
HTH,
Pascal
Le 01/02/2013 16:32, Janesh Devkota a écrit :
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
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