Could anyone tell me a better way to achieve the output of this for loop? It
seems to run quite slow. I'm sure there must be a more consise way to sum
from FN to LN, excluding positive values, for each row.
#sum between FN and LN, excluding positive values
for(i in 1:R){
for(j in FN[i]:LN[i]){
if
Here is the full code:
R <- 5328
#Temp is a temperature file with daily temp. values for each day of the
year, for 5328 locations
Temp <- rnorm(100)
dim(Temp) <- c(365,5328)
# transpose temp dataframe in order to perform rollmean (running mean) on
proper data section
Temp_T <- t(Temp)
library(zoo
Hello,
I have the following data frame (DF):
V5V5.1V5.2 V5.3 V5.4 V5.5
2 -5890.18905 -6019.84665 -6211.06545 -6198.9353 -6616.8677 -6498.7183
3 -5890.18905 -6019.84665 -6211.06545 -6198.9353 -6616.8677 -6498.7183
4 -5890.18905 -6019.84665 -6211.06
Hello,
I have some R code that I wrote with version 2.8.1 and have since needed to
revert back to version 2.7.0 in order to run my R code with RPy for Python.
R version 2.7.1 is the latest version RPy supports. My issue is my code is
no longer running properly and I was hoping someone might be ab
a 31 day running mean along the 365 days.
I am new to R so any help would be greatly appreciated!
Thanks alot,
Rheannon
--
View this message in context:
http://www.nabble.com/rollmean%28%29-tp18366044p18366044.html
Sent from the R help mailing list archive at Nabble.com
r in a variable
Start <- i
I am getting a scripting out of bounds error and I suspect maybe the loop
isnt stoping at the end of the matrix?
Any help is greatly appreciated!
Cheers,
Rheannon
--
View this message in context:
http://www.nabble.com/While-loop-tp18408462p18408462.html
Sent from
Hello,
I am trying to select the following headers from a data frame but when I try
and run the command it executes halfway through and give me an error at V188
and V359.
Temp <- data.frame(V4, V5, V6, V7, V8, V9, V10, V11, V12, V13, V14, V15,
V16, V17, V18, V19, V20, V21, V22, V23, V24, V25, V2
Hello,
I'd like to sum the values of a row from the first negative number (FN) to
the last negative number (LN), but not add any positive values to the sum.
Then apply this to each row of the data frame.
For example if I have a dataframe with Row 1 values
DF = (4, 3, 2, 1, 0, -1, -2, -3, -2, 2,
8 matches
Mail list logo