Hi,
Try:
df.1 <- read.table(text="Name network speed
Atlanta_Ga. LTE. 10
Hartford_CT. HSPA. 4
Seattle_WA. LTE.
12",sep="",header=TRUE,stringsAsFactors=FALSE)
df.1cleaned <- within(df.1,{ state <-gsub(".*\\_(.*)\\.$","\\1",Name);speed <-
speed*1000})
subset(df.1cleaned,network=="HSPA.") #check your number in speed column
# Name network speed state
#2 Hartford_CT. HSPA. 4000 CT
You could use ?lapply() for multiple dataframes
df.2 <- df.1
res <- lapply(list(df.1,df.2),function(x) {x1 <- within(x,{state <-
gsub(".*\\_(.*)\\.$","\\1",Name); speed <-
speed*1000});subset(x1,network=="HSPA.")})
names(res) <- paste0(c("df.1","df.2"),"cleaned")
res$df.2cleaned
A.K.
On Saturday, January 18, 2014 1:39 AM, Vijay <vijaychowdh...@gmail.com> wrote:
I have three data frames df.1, df.2 and df.3. All have the same structure I.e
here is df.1
Name network speed
Atlanta_Ga. LTE. 10
Hartford_CT. HSPA. 4
Seattle_WA. LTE. 12
I want to perform a couple of steps on each data frame and store the
transformed dataframes as df.1cleaned, df.2cleaned etc......
Here are the steps to perform.
1.Create a new column named state, given by the last two letters of the name
field
2. Only keep rows where network is HSPA
3. Multiple the speed column by 1000
So df.1cleaned would look like
Name Network. Speed. State
Hartford_CT. HSPA. 10000. CT
Can someone help me come up with a loop or a function that loops through all
dataframes and produces all three dataframes
Thanks
Vijay
Sent from my iPad
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