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 at 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:djmuser at 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, <Mohan.Radhakrishnan at cognizant.com>
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
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