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Given the following setup:
area.factor <- cut(state.x77[,"Area"],
breaks=quantile(state.x77[,"Area"],c(0,.25,.75,1)),
labels=c("small","medium","large"),
include.lowest=TRUE)
state <- data.frame(pop=state.x77[,"Population"],
inc=state.x77[,"Income"],
area=area.factor,
region=state.region)
pop.area.region <- with(state,ftable(pop,area,region))
The following two lines of code are show the same result:
head(ftable(prop.table(pop.area.region,margin=2)))
head(prop.table(pop.area.region,margin=2))
I don't understand what effect adding ftable has, if any, in:
head(ftable(prop.table(pop.area.region,margin=2)))
Adding ftable witll try to coerce the pop.area.region to a ftable class. Here
No need to add ftable since pop.area.region is already an ftable.
identical(ftable(prop.table(pop.area.region,margin=2)),
prop.table(pop.area.region,margin=2))
TRUE
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Looking for other way than ifelse.
How to create NewColumn like this:
As displayed in your picture, you want to paste together two columns. Assuming your dataframe is called df, you can do:
df$NewColumn <- paste(df$Column2,"",df$Column1)
Which will get you the outcome in the picture.
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Is there a function such as kable to output character vectors in a way that doesn't look as ugly as the default console type?
See eg p from the pander package or the generic pander method:
> pander::pander(sample(letters, 5))
_p_, _r_, _v_, _f_ and _t_
If you want to override the default formatting, see panderOptions or specify directly in the p function.
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I am having trouble operating Matrixs.
First, I want to make factor data to integer so i can operate.
Second, The First col, which shows date, should be factor. How can i change?
Try this:
d <- data.frame(1:10, letters[1:10])
data.matrix(d)
Also you can try this too :
m = matrix(scan("file.csv", what=numeric(), skip=1))
skip=1 to skip a header line.
Hope this will help you
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For the auto.arima function in forecast package of R, is there a way to let the function omit a model of arima(0,0,0), as I simply assume there must be some correlation within the dataset.
You could try looking at the help for the function
auto.arima(). Check the arguments start.p, start.q,
d,max.d
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I have data that contains 14 columns of predictors and 1 column of solution variable(y).
I wanted to know if there are any inbuilt functions to normalize and denormalize data in R.
Thank you.
normDataWithin of package {Rmisc} can be used: http://www.inside-r.org/packages/cran/Rmisc/docs/normDataWithin
Else following methods can be used:
(variable-mean)/sd . Following code can be used for a data.frame:
mydata$myNormalizedVar<-(mydata$myvar-mean(mydata$myvar))/sd(myvar)
log (log10), log2, and square root (sqrt)
Normal quantile normalization or normal quantile transformation. Try:
quantNorm = function(x){qnorm(rank(x,ties.method = "average")/(length(x)+1))}
hist(quantNorm(1:10000),100)