Findpeaks in geom_points

[HelloWorld1]

Hello

I am new to Rstudio. I have currently created gg geom point plots more like a periodic graph of ecg. I would like to find R points. I have currently imported csv file while consists of time in column 1 and mV in column 2 and based on this table, I have created a plot.

ggplot(test3, aes(x = time, y = ekg)) +
geom_point() +
xlim(0,2)

I have found a function called findPeaks function to find a R points in this plot. How should I use this function to indicate R points in geom plot and store this mV values and time stamp of this mV values in another table?

[Z3tt]

Hi HelloWorld1 and welcome to the Rstudio community! Glad to hear you found you're way to Rstudio (and as it sounds you are also using R for the first time - R is the programming language, Rstudie the integrated development environment).

Usually it is common practice to also share the data, or at least a subset, so others can reproduce your steps. You can simply copy the output dput(your_data) so others can directly include it in their scripts.

Now to your question: I assume that you have a data frame consisting not only of two but three rows - otherwise your code owuld not work. So your data frame called test3 likely looks like this:

time | mv  | ekg
x1   | y1  | z1
x2   | y2  | z2
...  | ... | ... 
xn   | yn  | zn

If you are referrring to this function called findPeaks() from the {quantmod} package, it does calculate the peaks in your data before passing it to ggplot().

I have never used it before (I have expected that it returns the high values) but here you go:

library(tidyverse)
library(quantmod)

## some random data
test3 <- tibble(
    time = 1:10,
    mv = runif(10, 0, 1),
    ekg = rnorm(10, 0, 1)
  ) %>% 
  mutate(id = row_number())

test3
#> # A tibble: 10 x 4
#>     time     mv     ekg    id
#>    <int>  <dbl>   <dbl> <int>
#>  1     1 0.745  -0.0670     1
#>  2     2 0.766   1.10       2
#>  3     3 0.752   1.18       3
#>  4     4 0.941  -0.138      4
#>  5     5 0.358  -0.588      5
#>  6     6 0.0430 -0.918      6
#>  7     7 0.738  -1.33       7
#>  8     8 0.624   1.37       8
#>  9     9 0.243  -0.0739     9
#> 10    10 0.770   0.199     10

peaks <- findPeaks(test3$ekg, thresh = 1)

## either add as additional layer and overplot black points
ggplot(test3, aes(x = time, y = ekg)) +
  geom_point() +
  geom_point(data = filter(test3, id %in% peaks), color = "red")

## ... or add a column and map color to that:
test3 %>% 
  mutate(peak = if_else(id %in% peaks, T, F)) %>% 
  ggplot(aes(x = time, y = ekg, color = peak)) +
  geom_point() +
  scale_color_manual(values = c("black", "red"))

^{Created on 2020-06-29 by the reprex package (v0.3.0)}