[R] Error bars and CI

[Mohan.Radhakrishnan at cognizant.com]

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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