I have a task to upload excel files to disk.
That is, there is a link to the drive like https://drive.google.com/drive/u/1/folders/1RB_9wvdu2mos6lCMpQqiTF0c
and files on the computer
I found the googlesheets library but I don’t fully understand how to use, for example, the function drive_upload to do what I need
setwd() to drive does not working either
Related
I have used google drive as a repository of my SAS and R projects. Gdrive search tool cannot search through these codes. Is there a desktop or online-based app that can be linked to google drive to perform such searches?
Someone uploaded a folder on Google Drive and shared it with me. I installed Google Colab and opened an IPhython notebook in colab. For connecting it with Google Drive, I did:
from google.colab import drive
drive.mount('/content/gdrive')
I continued to run the code and do some imports, and at some point I need to give the path for this folder. I tried:
path = "/content/gdrive/MyDrive/the_folder/"
But when I checked on the left-hand-side, under "Files"->"gdrive"->"MyDrive", it's not even there, so no wonder it's not found when I run the code later. Did I mount it incorrectly?
In case you want to work with a shared by someone Google Drive folder (you are not an owner of which) in Google Colab, you should, first of all, create a shortcut of this folder inside your Drive, as it exists in the Drive of its owner.
It can be done following way: right-click on this folder while in the Shared with me tab of the Google Drive and then click on the Add shortcut to Drive. This way your Drive will contain the folder (a shortcut), which was created and shared by someone else.
Then, after a regular mount procedure this folder will be accessible from Google Colab.
Im tring to create a shiny app that read and online onedrive xlsx file and show some things, but for the moment Im unable to read the onedrive xlsx file, I already explore the Microsoft365R and I can conect to my onedrive and I even can open the fil but... what it does is from r open a tab in chrome with the excel file.
I need the file in the local enviroment of r.. this its beacause the shiny app must be deploy in a web server, that every time the app runs it reads the update the file.
library(Microsfot365R)
odb <- get_business_onedrive()
odb$open_file("lcursos.xlsx")
Also this its a business account, so I also have to put the username and key to acces each file, that its beacause use the simple url doesnt work, it says Error 403 FORBIDEEN.
Any ideas?
Thank you so much!
Use the download_file() method to download the file to your local machine:
odb$download_file("lcursos.xlsx")
You can set the location of the download with the dest argument. Once it's downloaded, open it with the xls reader package of your choice. I suggest either openxlsx or readxl.
Note that if your file is password protected, your options are limited. See this question for possible solutions.
How to load CSV files in google colab for R?
For python, there are many answers but can someone guide how file can be imported in R for google colab.
Assuming you mean "get a CSV file from my local system into the Colaboratory Environment" and not just importing it from inside the Colab file paths as per Korakot's suggestion, since your question wasn't very clear, I think you have two main options:
1. Upload a file directly through the shortcut in the side menu thingy.
Just click the icon there and upload your file to drive. Then, you can run normal r import functions by following the internal path like korakot put in this answer.
2. Connect your google drive
Assuming you're using a notebook like the one created by Thong Nguyen, you can use a python call to mount your own google drive, like this one:
cat(system('python3 -c "from google.colab import drive\ndrive.mount()"', intern=TRUE), sep='\n', wait=TRUE)
... which will initiate the login process to Google Drive and will allow you to access your files from google drive as if they were folders in colab. There's more info about this process here.
In case you use the Colab with R as runtime type (and Python code would not work therefore), you could also simply upload the file as MAIAkoVSky suggested in step 1 and then import it with
data <- read.csv('/content/your-file-name-here.csv')
The filepath can also be accessed by right clicking on the file in the interface.
Please be aware that the files will disappear once you disconnected from Colab. You would need to upload them again for the next session.
You can call the read.csv function like
data = read.csv('sample_data/mnist_test.csv')
I'm currently doing a project that uses R to process some large csv files that are saved in my local directory linked to my repo.
So far, I managed to create the R project and commit and push R scripts into the repo with no problem.
However, the scripts read in the data from the csv files saved in my local directory, so the code goes in a form
df <- read.csv("mylocaldirectorylink")
However, this is not helpful if my partner and I working on the same project have to change that url to our own local directory every time we pull it off the repo. So I was thinking that maybe we can upload the csv files onto GitHub Repo and let the R script refer directly to the csv files online.
So my questions are:
Why can't I upload csv files onto GitHub? They keep saying that my file is too large.
If I can upload the csv files, how to I read the data from these csv files?
Firstly, it's generally a bad idea to store data on Github, especially if it's large. If you want to save it somewhere on the Internet, you can use, say, Dataverse, and then can access your data with URL (through the API), or Google Drive, as Jake Kaupp suggested.
Now back to your question. If your data doesn't change, I would just use not the absolute paths to CSV but relative ones. In other words, instead of
df<-read.csv("C:/folder/subfolder/data.csv")
I would use
df <- read.csv("../data.csv")
If you are working with R project, then the initial working directory is inside the folder of the project. You can check it with getwd(). This working directory changes as you move the R project. Just agree with your colleague that your data file should be in the same folder where the folder with R project is situated.
This is for a Python script.
You can track csv files by editing your .gitignore file.
**OR**
You can add csv files in your github repo, which can be used by others.
I did so by following steps:
Checkout the branch on github.com
Go to the folder where you want to keep csv files.
Here, you will see an option "Add file" in top right area as shown below:
Here you can upload csv files and commit the changes in same branch or by creating a new branch.