Yes. I tried that already. Not straightforward.
data <- read.csv("20_newsgroups.csv",fill=TRUE,as.is=T,header=F, quote="",
sep=",", encoding="UTF-8")
This line does read it haphazardly. The emails in the column are split into
multiple columns and there are several columns with just ‘NA’. Totall
Hi,
Reading http://ssc.wisc.edu/~ahanna/20_newsgroups.csv after downloading it using
data <- read.csv("20_newsgroups.csv",header=TRUE)
throws this.
Warning message:
In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
EOF within quoted string
So, for example, the first lin
Hi,
I am trying to extract an attribute value which is like this.
(e.g) class="whQuestion"
The 'extract' function prints this. But I am not sure how to get "whQuestion"
from that. The type of 'x' in extract
is "character"
[1] "XMLAttributeValue"
class
"whQuestion"
attr(,"class")
extrac
I am replying to my question.
AFAIK dplyr works only with data frames.
So I flattened the RC's like this. A pure OO approach and a functional
representation of it are at loggerheads. I think.
filteredmeasurements <-
keep(measure
Hi,
I have a hierarchy of such classes. Subject has a list of measurements. Let
assume I have a list of such 'Subject' RC's.
Can I use dplyr to navigate from Subject to the list of measurement RC's and
filter and group data ? dplyr should
be able to call the methods on these RC's to operate on
Hi,
The last line should give me the value of 'amount'. Is the syntax wrong ?
Measurement <- setRefClass("Measurement",
fields = list(subject = Subject,
quantity = Quantity))
s <- Subject$new(id = 100)
u <- CompoundUnit$new( micrograms = 100,
Hi
I am trying to simulate task estimation person days using this type of R
code. But I am not sure about reasoning here. Should the distribution be beta
or triangular or something else ? How do we get the values of mu,z and s here ?
Are there any explanations available ? Sections of some b
Hi,
I am a developer and I code 'R'. We have some project tasks and
durations(Expected, 50% - Average Case and 90% - Worst Case ) and I am trying
to understand how a simulation of this using monte carlo would help. Most of
the websites deal with either the math or some commercial package.
Hi Dennis,
I have copied the 'r' group. Could you explain ? Why
can't we compute CI and error bars using this data set ?
The graph generated has equal-sized error bars and a 99% confidence band.
Groups are not needed here. But the error bar and CI calculations could be
i
I think it could be something like this. But the mean is for the entire set.
Not groups.
I get a graph with this code but error bars are not there.
p<-ggplot(jc,aes(IDX,V1,colour=V1))
p <- p + stat_summary(fun.y=mean,geom="point")
p <- p + stat_summary(fun.y=mean,geom="line")
p <- p + stat_summa
Your sample code is working. But I am missing the logic when my dataset is
involved.
My full dataset is this. It is the V1 column I am interested in. I am not
'grouping' here.
V1 IDX
1 0.796 1
2 0.542 2
3 0.510 3
4 0.617 4
5 0.482 5
6 0.387 6
7 0.272 7
8 0.536 8
9
Hi,
I want to plot a line graph using this data. IDX is x-axis and V1 is y-axis. I
also want standard error bars and 99% CI to be shown. My code is given below.
The section that plots the graph is the problem. I don't see all the points in
the line graph with error bars. How can I also show t
12 matches
Mail list logo