I am relatively new to R and am having some trouble with how to access my data. I have my test.xls file created in my MYDocuments. How to I access it from R
library(xlsReadWrite)
DF1 <- read.xls("test.xls") # read 1st sheet
Set the working directory with:
setwd("C:/Documents and Settings/yourname/My Documents")
This link may be useful as a method of making working folders per project and then placing all relevant info in that folder. It's a nice tutorial for making project files that contain everything you need. This is one approach.
http://www.dangoldstein.com/flash/Rtutorial2/Rtutorial2.html
The setwd() is another approach. I use a combination of the two in my work.
Related
I have 3 r scripts;
data1.r
data2.r
graph1.r
the two data files, run some math and generate 2 separate data files, which I save in my working directory. I then call these two files in graph1.r and use it to plot the data.
How can I organise and create an R project which has;
these two data files - data1.r and data2.r
another file which calls these files (graph1.r)
Output of graph1.r
I would then like to share all of this on GitHub (I know how to do this part).
Edit -
Here is the data1 script
df1 <- data.frame(x = seq(1,100,1), y=rnorm(100))
save(df1, file = "data1.Rda")
Here is the data2 script
df2 <- data.frame(x = seq(1,100,1), y=rnorm(100))
save(df2, file = "data2.Rda")
Here is the graph1 script
load(file = "data1.Rda")
load(file = "data2.Rda")
library(ggplot2)
ggplot()+geom_point(data= df1, aes(x=x,y=y))+geom_point(data= df2, aes(x=x,y=y))
Question worded differently -
How would the above need to be executed inside a project?
I have looked at the following tutorials -
https://r4ds.had.co.nz/workflow-projects.html
https://martinctc.github.io/blog/rstudio-projects-and-working-directories-a-beginner's-guide/
https://swcarpentry.github.io/r-novice-gapminder/02-project-intro/
https://www.tidyverse.org/blog/2017/12/workflow-vs-script/
https://chrisvoncsefalvay.com/2018/08/09/structuring-r-projects/
https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects
I have broken my answer into three parts:
The question in your title
The reworded question in your text
What I, based on your comments, believe you are actually asking
How to transfer my files to R Projects, and then to GitHub?
From RStudio, just create a new project and move your files to this folder. You can then initialize this folder with git using git init.
How would [my included code] need to be executed inside a project?
You don't need to change anything in your example code. If you just place your files in a project folder they will run just fine.
An R project mainly takes care of the following for you:
Working directory (it's always set to the project folder)
File paths (all paths are relative to the project root folder)
Settings (you can set project specific settings)
Further, many external packages are meant to work with projects, making many task easier for you. A project is also a very good starting point for sharing your code with Git.
What would be a good workflow for working with multiple scripts in an R project?
One common way of organizing multiple scripts is to make a new script calling the other scripts in order. Typically, I number the scripts so it's easy to see the order to call them. For example, here I would create 00_main.R and include the code:
source("01_data.R")
source("02_data.R")
source("03_graph.R")
Note that I've renamed your scripts to make the order clear.
In your code, you do not need to save the data to pass it between the scripts. The above code would run just fine if you delete the save() and load() parts of your code. The objects created by the scripts would still be in your global environment, ready for the next script to use them.
If you do need to save your data, I would save it to a folder named data/. The output from your plot I would probably save to outputs/ or plots/.
When you get used to working with R, the next step to organize your code is probably to create a package instead of using only a project. You can find all the information you need in this book.
I'm no R-programmer (because of the problem I started learning it), I'm using Python, In a forcasting task I got a dataset signalList.rdata of a pheomenen called partial discharge.
I tried some commands to load, open and view, Hardly got a glimps
my_data <- get(load('C:/Users/Zack-PC/Desktop/Study/Data Sets/pdCluster/signalList.Rdata'))
but, since i lack deep knowledge about R, I wanted to convert it into a csv file, or any type that I can deal with in python.
or, explore it and copy-paste manually.
so, i'm asking for any solution whether using R or Python or any tool to get what's in the .rdata file.
Have you managed to load the data successfully into your working environment?
If so, write.csv is the function you are looking for.
If not,
setwd("C:/Users/Zack-PC/Desktop/Study/Data Sets/pdCluster/")
signalList <- load("signalList.Rdata")
write.csv(signalList, "signalList.csv")
should do the trick.
If you would like to remove signalList from your working directory,
rm(signalList)
will accomplish this.
Note: changing your working directory isn't necessary, it just makes it easier to read in a comment I feel. You may also specify another path for saving your csv to within the second argument of write.csv.
I am a new user of blogdown using Hugo. I would like to create a new post that includes R code to read a data file.
The data file is in my static folder, local path C:\mydir\myblogdown\static\data\savedrecs.txt. Since I was successful in referring to an image using a relative path like this, , I tried reading the data using something similar for the data file, read.csv("/data\savedrecs.txt"), but that didn't work.
I started playing around with the list.files() function to see if I could find a relative path that worked in my local version of the post, list.files("../../static/data") worked, showing me ## [1] "savedrecs.txt".
I tried searching around other folks' blogdown repos on Github to see how they might have referred to a data file, but the only example I found referred to a data file using a URL.
I suspect that this may be due to the location of your data file. In my working example, the Rmd form of my blog post is in the directory, called p0bs/content/post. I also add my data file (a CSV in my case) to this directory.
I then treat the rest of the post as I would in a standard Rmarkdown website, with Rmd chunks (that are named without spaces). In your case, that code would include:
read.csv("savedrecs.txt")
I hope that helps you.
I have a few R files that contain functions imported and used by several other R files. I import these functions with the source function. Naturally, the scope of a particular file might change over time, and recently I wanted to rename a file I had already sourced in many other places.
I'm using RStudio, and I have been unable to find a way to do this except for either manually updating each dependent file, or creating some external code to scan through the files.
Is there no way to do consistent renaming in RStudio? Alternatively, am I doing something wrong by using source to add functions?
You may or may not find this satisfactory. Create a parent script with the old name that sources the script with the new name.
Extending this, you could just create a general preamble script, called something like "preamble.R", that sources all general utility scripts you have. Such an approach is common (I believe) with TeX. Then you only have one place to update file names.
While developing a package I encountered the problem of supplementary data import - this has been 'kind of' solved here.
Nevertheless, I need to make use of a function of another package, which needs a path to the used file. Sadly, using GlobalEnvironment variables here is not an option.
[By the way: the file needs to be .txt, while supplementary data should be .RData. The function is quite picky.]
So I need to know how to get the path supplementary data file of a package. Is this even possible to do?
I had the idea of reading the .RData into the global environment and then saving it into a tmpfile for further processing. I would really like to know a clean way - the supplementary data is ~100MB large...
Thank you very much!
Use system.file() to reliably find the path to the installed package and sub-directories, typically these are created in your-pkg-source/inst/extdata/your-file.txt and then referenced as
system.file(package="your-pkg", "extdata", "your-file.txt")