Hi Nancy,
The chickwts dataset contains one sort-of continuous variable (weight)
and a categorical variable (feed). Two things that will help you to
understand what you are trying to do is to "eyeball" the "weight"
data:
# this shows you the rough distribution of chick weights
hist(chickwts$weight
Hi,
I found the following relationship:
it is given
x is a vector, bm1 and bm2 are vectors of type logical end exactly as long as x
then the following formula returns alwasy TRUE:
all( x[ bm1 & bm2] == x[ bm2][ bm1[ bm2]] )
.
I think it is no such great deal and a lot of R programmers will k
Thank you so much this worked wonderfully!
On Sat, Oct 5, 2019 at 4:05 PM Rui Barradas wrote:
>
> Hello,
>
> Please CC the list.
>
> The following code does what you want.
>
> tot <- data.frame(a = c("E10123", "F123", "G4567"),
>b = c("a123", "E112345", "b456"))
>
> e10 <- sap
Hello,
Please CC the list.
The following code does what you want.
tot <- data.frame(a = c("E10123", "F123", "G4567"),
b = c("a123", "E112345", "b456"))
e10 <- sapply(tot, function(x) grepl("^E10", x))
e10 <- rowSums(e10) > 0
e11 <- sapply(tot, function(x) grepl("^E11", x))
e1
Hello,
Try the following
cols <- sapply(tot, function(x) any(grepl("^E94", x)))
To have the column numbers,
which(cols)
Hope this helps,
Rui Barradas
Às 19:50 de 05/10/19, Ana Marija escreveu:
Hello,
I have a data frame tot which has many columns and many rows.
I am trying to find all c
Hello,
I have a data frame tot which has many columns and many rows.
I am trying to find all columns that have say a value in any of their
rows that STARTS WITH: "E94"
for example there are columns like this:
> unique(tot$diagnoses_icd9_f41271_0_44)
[1] NA "E9420"
I tried:
s=select(tot,st
Categorical data cannot be normal. What you are doing is statistical
nonsense, as your error messages suggest. You need to consult a local
statistician for help.
Furthermore, statistical questions are generally OT on this list, which is
about R programming.
Bert Gunter
"The trouble with having
Hello
I have data that are categorical both independent variable and dependent as
well having levels more than 3. How can i check the normality of my data?
I have tried the example given of Shapiro-Wilk for levels of factors
data
summary(chickwts)
## linear model and ANOVA
fm <- lm(weight ~ feed
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