Re: [R] EOF within quoted string
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’. Totally 202
columns.
And then I removed columns with NA’s and concatenated all the text and finally
got it.
munged <- data[, unlist(lapply(data, function(x) !all(is.na(x]
munged <- munged[-1,]
munged$text <- apply( munged[ , c(3:ncol(munged)) ] , 1 , paste0 , collapse = "
")
munged <- munged[,c("V1","V2","text")]
print(head(munged$text))
Mohan
From: Adams, Jean [mailto:jvad...@usgs.gov]
Sent: Thursday, August 10, 2017 8:03 PM
To: Radhakrishnan, Mohan (Cognizant)
Cc: R help
Subject: Re: [R] EOF within quoted string
You might want to try some of the suggestions mentioned in this post:
https://stackoverflow.com/q/17414776/2140956
Jean
On Thu, Aug 10, 2017 at 7:59 AM,
mailto:mohan.radhakrish...@cognizant.com>>
wrote:
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 line in the file is this. This column contains only
such text. Is there a way read it ?
From: cub...@garnet.berkeley.edu () Subject:
Re: Cubs behind Marlins? How? Article-I.D.: agate.1pt592$f9a Organization:
University of California, Berkeley Lines: 12 NNTP-Posting-Host:
garnet.berkeley.edu
gajar...@pilot.njin.net writes: morgan and
guzman will have era's 1 run higher than last year, and the cubs will be
idiots and not pitch harkey as much as hibbard. castillo won't be good (i
think he's a stud pitcher) This season so far, Morgan and Guzman helped
to lead the Cubsat top in ERA, even better than THE rotation at
Atlanta.Cubs ERA at 0.056 while Braves at 0.059. We know it is early
in the season, we Cubs fans have learned how to enjoy theshort
triumph while it is still there.
Thanks,
Mohan
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[R] EOF within quoted string
Hi,
Reading http://ssc.wisc.edu/~ahanna/20_newsgroups.csv after downloading it using
data <- read.csv("20_newsgroups.csv",header=TRUE)
throws this.
Warning message:
In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
EOF within quoted string
So, for example, the first line in the file is this. This column contains only
such text. Is there a way read it ?
From: cub...@garnet.berkeley.edu () Subject: Re: Cubs behind Marlins? How?
Article-I.D.: agate.1pt592$f9a Organization: University of California, Berkeley
Lines: 12 NNTP-Posting-Host: garnet.berkeley.edu gajar...@pilot.njin.net
writes: morgan and guzman will have era's 1 run higher than last year, and
the cubs will be idiots and not pitch harkey as much as hibbard. castillo
won't be good (i think he's a stud pitcher) This season so far, Morgan
and Guzman helped to lead the Cubsat top in ERA, even better than THE
rotation at Atlanta.Cubs ERA at 0.056 while Braves at 0.059. We know it
is earlyin the season, we Cubs fans have learned how to enjoy the
short triumph while it is still there.
Thanks,
Mohan
This e-mail and any files transmitted with it are for the sole use of the
intended recipient(s) and may contain confidential and privileged information.
If you are not the intended recipient(s), please reply to the sender and
destroy all copies of the original message. Any unauthorized review, use,
disclosure, dissemination, forwarding, printing or copying of this email,
and/or any action taken in reliance on the contents of this e-mail is strictly
prohibited and may be unlawful. Where permitted by applicable law, this e-mail
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be monitored.
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[R] Extract XMLAtrributeValue
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")
extract <- function(x){
print(x)
}
filteredclasses <-
function(){
classes <- xpathSApply(doc = posts, path = "/*/Posts/Post/@class", extract)
}
Thanks,
Mohan
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Re: [R] Operating on RC in a list
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(measurements, function(x){
x$getid() ==
subject$getid()
})
groupedmeasurements <-
filteredmeasurements %>%
lapply(function(x){
m <<- x$getmeasurement()
as.data.frame(list('visit'=m$getvisit(),
'location'=x$getlocation()$getlocation(),
'amount'=m$getquantity()$amount))
}) %>% rbind_all()
dataColumns <- c('amount')
ddply(groupedmeasurements,c('visit','location'),function(x)
colSums(x[dataColumns]))
Thanks,
Mohan
From: Radhakrishnan, Mohan (Cognizant)
Sent: Wednesday, June 07, 2017 2:05 PM
To: r-help@r-project.org
Subject: Operating on RC in a list
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 the data structure ?
I tried to coerce the list of RC's into a data frame unsuccessfully. But dplyr
should be able to work with lists too. Right ?
Subject <- setRefClass("Subject",
fields = list( id = "numeric",
measurement = "Measurement",
location = "Location"),
methods=list(getmeasurement = function()
{
measurement
},
getid = function()
{
id
},
getlocation = function()
{
location
},
summary = function()#Implement other summary methods in appropriate objects as
per their responsibilities
{
paste("Subject summary ID [",id,"] Location [",location$summary(),"]")
},show = function(){
cat("Subject summary ID [",id,"] Location [",location$summary(),"]\n")
})
)
Thanks,
Mohan
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[R] Operating on RC in a list
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 the data structure ?
I tried to coerce the list of RC's into a data frame unsuccessfully. But dplyr
should be able to work with lists too. Right ?
Subject <- setRefClass("Subject",
fields = list( id = "numeric",
measurement = "Measurement",
location = "Location"),
methods=list(getmeasurement = function()
{
measurement
},
getid = function()
{
id
},
getlocation = function()
{
location
},
summary = function()#Implement other summary methods in appropriate objects as
per their responsibilities
{
paste("Subject summary ID [",id,"] Location [",location$summary(),"]")
},show = function(){
cat("Subject summary ID [",id,"] Location [",location$summary(),"]\n")
})
)
Thanks,
Mohan
This e-mail and any files transmitted with it are for the sole use of the
intended recipient(s) and may contain confidential and privileged information.
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destroy all copies of the original message. Any unauthorized review, use,
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and provide commented, minimal, self-contained, reproducible code.
[R] RC class composition
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,
cubicmeter = 1 )
q <- Quantity$new(amount = 100,
units = u )
m <- Measurement$new(subject = s,
quantity = q)
print( m$quantity$amount )
Thanks,
Mohan
This e-mail and any files transmitted with it are for the sole use of the
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If you are not the intended recipient(s), please reply to the sender and
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and provide commented, minimal, self-contained, reproducible code.
[R] Task estimation - Monte Carlo
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 book ?
I have the book about monte carlo analysis using R but that looks like the next
step for me. I am at a preliminary stage.
taskestimation <- function( low , high, ci=0.9, n=1) {
mu = mean(c(low,high))
z = qnorm(1-(1-ci)/2)
s = (high - mu)/z
rnorm(n, mu, s)
}
result = taskestimation(10,80)
#calculate the percentage of cases below certain number of days
length(result[result < 50])/length(result)
I am able to plot a density curve showing the percentage of completion below
'50' days that the simulation predicts.
Thanks,
Mohan
This e-mail and any files transmitted with it are for the sole use of the
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If you are not the intended recipient(s), please reply to the sender and
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and provide commented, minimal, self-contained, reproducible code.
[R] Simple monte carlo
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. I don't want to use Excel because I use Eclipse StatET environment. What kind of distribution should I use ? Is there a simpler explanation of a practical schedule distribution calculation ? Thanks, Mohan This e-mail and any files transmitted with it are for the sole use of the intended recipient(s) and may contain confidential and privileged information. If you are not the intended recipient(s), please reply to the sender and destroy all copies of the original message. Any unauthorized review, use, disclosure, dissemination, forwarding, printing or copying of this email, and/or any action taken in reliance on the contents of this e-mail is strictly prohibited and may be unlawful. Where permitted by applicable law, this e-mail and other e-mail communications sent to and from Cognizant e-mail addresses may be monitored. [[alternative HTML version deleted]] __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Error bars and CI
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
incorrect but I am able to draw this.
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 0.498 9
10 0.402 10
11 0.328 11
12 0.542 12
13 0.299 13
14 0.647 14
15 0.291 15
16 0.815 16
17 0.680 17
18 0.363 18
19 0.560 19
20 0.334 20
Assume the dataframe is 'jc'.
print(summary(jc$V1))
error <- qt(0.995,df=length(jc$V1)-1)*sd(jc$V1)/sqrt(length(jc$V1))
error1 <- mean(jc$V1)-error
error2 <- mean(jc$V1)+error
print(error1)
print(error2)
q <- qplot(geom = "line",jc$IDX,jc$V1,
colour='red')+geom_errorbar(aes(x=jc$IDX, ymin=jc$V1-sd(jc$V1),
ymax=jc$V1+sd(jc$V1)), width=0.25)+
geom_ribbon(aes(x=jc$IDX, y=jc$V1, ymin=error1,
ymax=error2),fill="ivory2",alpha = 0.4)+
xlab('Iterations') + ylab("Java Collections")+theme_bw()
Thanks,
Mohan
-Original Message-
From: Dennis Murphy [mailto:djmu...@gmail.com]
Sent: Wednesday, June 17, 2015 8:42 PM
To: Radhakrishnan, Mohan (Cognizant)
Subject: Re: [R] Error bars and CI
Q: How do you expect to get error bars when you plot "groups" having samples of
size 1? If you "are not grouping", then what is the point of trying to
manufacture variation where none exists? I'd suggest you think a little more
deeply about what you can achieve with the available data.
This plot visualizes the data you posted. Every point is accounted for. I named
the input data frame DF.
ggplot(DF, aes(x = IDX, y = V1)) +
geom_line() + geom_point()
If you don't have replicate data at each unique x-value you want to plot, you
cannot legitimately plot error bars, confidence intervals or any other visual
that describes a (summary of) a distribution. If the values of V1 are supposed
to represent averages that come from other data set, then you should have a
corresponding column of standard deviations/standard errors, and *then* you can
plot error bars, CIs, etc. Without a legitimate measure of variation in your
input data frame, I don't see how you can possibly generate a line graph with
accompanying error bars/CIs.
Dennis
On Wed, Jun 17, 2015 at 1:13 AM, wrote:
> 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_summary(fun.data=mean_cl_normal,conf.int = .99,
> geom="errorbar", width=0.2)
>
>
> Thanks,
> Mohan
>
> -Original Message-
> From: Radhakrishnan, Mohan (Cognizant)
> Sent: Wednesday, June 17, 2015 12:54 PM
> To: 'Dennis Murphy'
> Cc: r-help@r-project.org
> Subject: RE: [R] Error bars and CI
>
> 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 0.498 9
> 10 0.402 10
> 11 0.328 11
> 12 0.542 12
> 13 0.299 13
> 14 0.647 14
> 15 0.291 15
> 16 0.815 16
> 17 0.680 17
> 18 0.363 18
> 19 0.560 19
> 20 0.334 20
>
> Thanks,
> Mohan
>
> -Original Message-
> From: Dennis Murphy [mailto:djmu...@gmail.com]
> Sent: Tuesday, June 16, 2015 1:18 AM
> To: Radhakrishnan, Mohan (Cognizant)
> Subject: Re: [R] Error bars and CI
>
> Hi:
>
> Firstly, your dplyr code to generate the summary data frame is unnecessary
> and distracting, particularly since you didn't provide the input data set;
> you are asked to provide a *minimal* reproducible example, which you could
> easily have done with a built-in data set.
> That said, to get what I perceive you want, I used the InsectSprays data from
> the autoloaded datasets package.
>
> # Function to compute standard error of a mean sem <- function(x)
> sqrt(var(x)/length(x))
>
> ## Use insectSprays data for illustration ## Compute mean and SE of
> count for each level of spray
>
> library(dplyr)
> library(ggplot2)
>
> insectSumm <- InsectSprays %>%
> group_by(spray) %>%
> summarise(mean = mean(count), se = sem(count))
>
>
> # Since the x-variable is a factor, need to map group = 1 to # draw lines
> between factor levels. geom_pointrange() can be # used to produce the 99% CIs
> per factor level, geom_errorbar() # for the mean +/- SE. I ordered the geoms
> so that the errorbar # is last, but if you want it (mostly) overwritten, put
> the # geom_pointrange() call last.
>
> ggplot(insectSumm, aes(x = spray, y = mean)) +
>theme_bw() +
>geom_line(ae
Re: [R] Error bars and CI
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_summary(fun.data=mean_cl_normal,conf.int = .99, geom="errorbar",
width=0.2)
Thanks,
Mohan
-Original Message-
From: Radhakrishnan, Mohan (Cognizant)
Sent: Wednesday, June 17, 2015 12:54 PM
To: 'Dennis Murphy'
Cc: r-help@r-project.org
Subject: RE: [R] Error bars and CI
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 0.498 9
10 0.402 10
11 0.328 11
12 0.542 12
13 0.299 13
14 0.647 14
15 0.291 15
16 0.815 16
17 0.680 17
18 0.363 18
19 0.560 19
20 0.334 20
Thanks,
Mohan
-Original Message-
From: Dennis Murphy [mailto:djmu...@gmail.com]
Sent: Tuesday, June 16, 2015 1:18 AM
To: Radhakrishnan, Mohan (Cognizant)
Subject: Re: [R] Error bars and CI
Hi:
Firstly, your dplyr code to generate the summary data frame is unnecessary and
distracting, particularly since you didn't provide the input data set; you are
asked to provide a *minimal* reproducible example, which you could easily have
done with a built-in data set.
That said, to get what I perceive you want, I used the InsectSprays data from
the autoloaded datasets package.
# Function to compute standard error of a mean sem <- function(x)
sqrt(var(x)/length(x))
## Use insectSprays data for illustration ## Compute mean and SE of count for
each level of spray
library(dplyr)
library(ggplot2)
insectSumm <- InsectSprays %>%
group_by(spray) %>%
summarise(mean = mean(count), se = sem(count))
# Since the x-variable is a factor, need to map group = 1 to # draw lines
between factor levels. geom_pointrange() can be # used to produce the 99% CIs
per factor level, geom_errorbar() # for the mean +/- SE. I ordered the geoms so
that the errorbar # is last, but if you want it (mostly) overwritten, put the #
geom_pointrange() call last.
ggplot(insectSumm, aes(x = spray, y = mean)) +
theme_bw() +
geom_line(aes(group = 1), size = 1, color = "darkorange") +
geom_pointrange(aes(ymin = mean - qt(.995, 11) * se,
ymax = mean + qt(.995, 11) * se),
size = 1.5, color = "firebrick") +
geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.2,
size = 1)
Clearly, you can pipe all the way through the ggplot() call, but I wanted to
check the contents of the summary data frame first.
Dennis
On Mon, Jun 15, 2015 at 3:51 AM, wrote:
> 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 the 99% CI in
> the graph ?
>
> V1 IDX
> 1 0.987 21
> 2 0.585 22
> 3 0.770 23
> 4 0.711 24
>
> library(stringr)
> library(dplyr)
> library(ggplot2)
>
> data <- read.table("D:\\jmh\\jmh.txt",sep="\t")
>
> final <-data %>%
>select(V1) %>%
> filter(grepl("^Iteration", V1)) %>%
> mutate(V1 = str_extract(V1, "\\d+\\.\\d*"))
>
> final <- mutate(final,IDX = 1:n())
>
> jc <- final %>%
> filter(IDX < 21)
>
>
> #Convert to numeric
> jc <- data.frame(sapply(jc, function(x) as.numeric(as.character(x
>
> print(jc)
>
> # The following section is the problem.
>
> sem <- function(x){
>sd(x)/sqrt(length(x))
> }
>
> meanvalue <- apply(jc,2,mean)
> semvalue <- apply(jc, 2, sem)
>
> mean_sem <- data.frame(mean= meanvalue, sem= semvalue,
> group=names(jc))
>
> #larger font
> theme_set(theme_gray(base_size = 20))
>
> #plot using ggplot
> p <- ggplot(mean_sem, aes(x=group, y=mean)) +
> geom_line(stat='identity') +
> geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem),
>width=.2)
> print(p)
>
> Thanks,
> Mohan
> This e-mail and any files transmitted with it are for the sole use of the
> intended recipient(s) and may contain confidential and privileged
> information. If you are not the intended recipient(s), please reply to the
> sender and destroy all copies of the original message. Any unauthorized
> review, use, disclosure, dissemination, forwarding, printing or copying of
> this email, and/or any action taken in reliance on the contents of this
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> applicable law, this e-mail and other e-mail communications sent to and from
> Cognizant e-mail addresses may be monitored.
>
>
Re: [R] Error bars and CI
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 0.498 9
10 0.402 10
11 0.328 11
12 0.542 12
13 0.299 13
14 0.647 14
15 0.291 15
16 0.815 16
17 0.680 17
18 0.363 18
19 0.560 19
20 0.334 20
Thanks,
Mohan
-Original Message-
From: Dennis Murphy [mailto:djmu...@gmail.com]
Sent: Tuesday, June 16, 2015 1:18 AM
To: Radhakrishnan, Mohan (Cognizant)
Subject: Re: [R] Error bars and CI
Hi:
Firstly, your dplyr code to generate the summary data frame is unnecessary and
distracting, particularly since you didn't provide the input data set; you are
asked to provide a *minimal* reproducible example, which you could easily have
done with a built-in data set.
That said, to get what I perceive you want, I used the InsectSprays data from
the autoloaded datasets package.
# Function to compute standard error of a mean sem <- function(x)
sqrt(var(x)/length(x))
## Use insectSprays data for illustration ## Compute mean and SE of count for
each level of spray
library(dplyr)
library(ggplot2)
insectSumm <- InsectSprays %>%
group_by(spray) %>%
summarise(mean = mean(count), se = sem(count))
# Since the x-variable is a factor, need to map group = 1 to # draw lines
between factor levels. geom_pointrange() can be # used to produce the 99% CIs
per factor level, geom_errorbar() # for the mean +/- SE. I ordered the geoms so
that the errorbar # is last, but if you want it (mostly) overwritten, put the #
geom_pointrange() call last.
ggplot(insectSumm, aes(x = spray, y = mean)) +
theme_bw() +
geom_line(aes(group = 1), size = 1, color = "darkorange") +
geom_pointrange(aes(ymin = mean - qt(.995, 11) * se,
ymax = mean + qt(.995, 11) * se),
size = 1.5, color = "firebrick") +
geom_errorbar(aes(ymin = mean - se, ymax = mean + se), width = 0.2,
size = 1)
Clearly, you can pipe all the way through the ggplot() call, but I wanted to
check the contents of the summary data frame first.
Dennis
On Mon, Jun 15, 2015 at 3:51 AM, wrote:
> 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 the 99% CI in
> the graph ?
>
> V1 IDX
> 1 0.987 21
> 2 0.585 22
> 3 0.770 23
> 4 0.711 24
>
> library(stringr)
> library(dplyr)
> library(ggplot2)
>
> data <- read.table("D:\\jmh\\jmh.txt",sep="\t")
>
> final <-data %>%
>select(V1) %>%
> filter(grepl("^Iteration", V1)) %>%
> mutate(V1 = str_extract(V1, "\\d+\\.\\d*"))
>
> final <- mutate(final,IDX = 1:n())
>
> jc <- final %>%
> filter(IDX < 21)
>
>
> #Convert to numeric
> jc <- data.frame(sapply(jc, function(x) as.numeric(as.character(x
>
> print(jc)
>
> # The following section is the problem.
>
> sem <- function(x){
>sd(x)/sqrt(length(x))
> }
>
> meanvalue <- apply(jc,2,mean)
> semvalue <- apply(jc, 2, sem)
>
> mean_sem <- data.frame(mean= meanvalue, sem= semvalue,
> group=names(jc))
>
> #larger font
> theme_set(theme_gray(base_size = 20))
>
> #plot using ggplot
> p <- ggplot(mean_sem, aes(x=group, y=mean)) +
> geom_line(stat='identity') +
> geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem),
>width=.2)
> print(p)
>
> Thanks,
> Mohan
> This e-mail and any files transmitted with it are for the sole use of the
> intended recipient(s) and may contain confidential and privileged
> information. If you are not the intended recipient(s), please reply to the
> sender and destroy all copies of the original message. Any unauthorized
> review, use, disclosure, dissemination, forwarding, printing or copying of
> this email, and/or any action taken in reliance on the contents of this
> e-mail is strictly prohibited and may be unlawful. Where permitted by
> applicable law, this e-mail and other e-mail communications sent to and from
> Cognizant e-mail addresses may be monitored.
>
> [[alternative HTML version deleted]]
>
> __
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
This e-mail and any files transmitted with it are for the sole use of the
intended recipient(s) and may contain confidential and privileged information.
If you are not the intended recipient(s), please reply to the send
[R] Error bars and CI
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 the 99% CI in the graph ?
V1 IDX
1 0.987 21
2 0.585 22
3 0.770 23
4 0.711 24
library(stringr)
library(dplyr)
library(ggplot2)
data <- read.table("D:\\jmh\\jmh.txt",sep="\t")
final <-data %>%
select(V1) %>%
filter(grepl("^Iteration", V1)) %>%
mutate(V1 = str_extract(V1, "\\d+\\.\\d*"))
final <- mutate(final,IDX = 1:n())
jc <- final %>%
filter(IDX < 21)
#Convert to numeric
jc <- data.frame(sapply(jc, function(x) as.numeric(as.character(x
print(jc)
# The following section is the problem.
sem <- function(x){
sd(x)/sqrt(length(x))
}
meanvalue <- apply(jc,2,mean)
semvalue <- apply(jc, 2, sem)
mean_sem <- data.frame(mean= meanvalue, sem= semvalue, group=names(jc))
#larger font
theme_set(theme_gray(base_size = 20))
#plot using ggplot
p <- ggplot(mean_sem, aes(x=group, y=mean)) +
geom_line(stat='identity') +
geom_errorbar(aes(ymin=mean-sem, ymax=mean+sem),
width=.2)
print(p)
Thanks,
Mohan
This e-mail and any files transmitted with it are for the sole use of the
intended recipient(s) and may contain confidential and privileged information.
If you are not the intended recipient(s), please reply to the sender and
destroy all copies of the original message. Any unauthorized review, use,
disclosure, dissemination, forwarding, printing or copying of this email,
and/or any action taken in reliance on the contents of this e-mail is strictly
prohibited and may be unlawful. Where permitted by applicable law, this e-mail
and other e-mail communications sent to and from Cognizant e-mail addresses may
be monitored.
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
