I want the results to be in a excel sheet.
The results should be made as a report.
I am testing a android device and want the result.
monkeyrunner
If you want to automate the whole process you can try xlwt podule to write Excel files from python.
If monkeyrunner gives you some problem importing python modules give AndroidViewClient/culebra a try.
Additionally, ask yourself whether you need Excel at all when you can generate nice reports from python using Sphinx or pod.
Related
I was trying to find a way to install modules permanently. I came to this post which teaches how to install packages on google drive, then mounting the drive and then using "sys.path.append" to tell the python where to look for the new package.
this method works as expected when a module directly is imported when you code in the notebook itself.
However, when I tried to run a project that I already had and wanted to run the .py file (by using"!python myCode.py"), the "sys" module can't append the path of the modules that have been installed in google drive.
in short, when you use the approach in the link above, you can only import packages when you directly code in the notebook itself. the approach did not work for me when I tried to use it on my .py files. i.e., when I used "!python myCode.py"
any suggestion on how to solve this problem? do you have the same problem as well?
thanks,
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 am looking for ways to process VSAM files with R and export as a csv.
I have been searching the web and have not been able to find any methods of using R to read VSAM files.
A little more information would be of use. How are you going to get the data from the VSAM files? Are you reading directly from an IBM system? What access method will you be using? What is the structure of the file you are reading since since if you want it to be put in a data.frame, is it something like a CSV file already?. So any other particulars would be helpful.
I have an iPad Pro as my primary computer, and am running R Studio from a cloud server for a class. I am trying to figure out how to import data sets, since my local working directory is on the server. I have been trying to download the package repmis, since I have been reading that that package allows for data set import from Dropbox. However, when I try to download the package, I get "Error:configuration failed for openssl" and a similar one for curl. I tried to install openssl but instead it says I need to install "deb" for ubuntu operating systems, but I can't find that in R Studio in the package database. (And I can't install curl without openssl either) Any suggestions?
If it's a relatively straightforward data set like a CSV, XML, JSON or even an .RData file you can use a Dropbox sharing URL to read it. Here's an example (it's a live URL) for reading in a CSV directly from a shared Dropbox link:
read.csv("https://www.dropbox.com/s/7xg5u0z1gtjcuol/mtcars.csv?dl=1")
The dl=1 won't be the default from a "share this link" copy (it'll probably be dl=0.
urla<- 'https://www.dropbox.com/s/fakecode/xyz.txt?raw=1'
bpdata<-read.table(urla, header=TRUE)
scode<-'https://www.dropbox.com/s/lp6fleehcsb3wi9/protoBP.R?raw=1'
source(scode)
readAndPlotZoomForYear(urla, 2019)
Basically I wanted to source code from a file in Dropbox and to use the read.table() function on a tab delineated data file. I found this could be done by replacing the string after the question mark with raw=1 in the Dropbox file links.
As part of a transition from MATLAB to R, I am trying to figure out how to read TDMS files created with National Instruments LabVIEW using R. TDMS is a fairly complex binary file format (http://www.ni.com/white-paper/5696/en/).
Add-ons exist for excel and open-office (http://www.ni.com/white-paper/3727/en/), and I could make something in LabVIEW to make the conversion, but I am looking for a solution that would let me read the TDMS files directly into R. This would allow us to test out the use of R for certain data processing requirements without changing what we do earlier in the data acquisition process. Having a simple process would also reduce the barriers to others trying out R for this purpose.
Does anyone have any experience with reading TDMS files directly into R, that they could share?
This is far from supporting all TDMS specifications but I started a port of a python npTDMS package into R here https://github.com/msuefishlab/tdmsreader and it has been tested out in the context of a shiny app here
You don't say if you need to automate the reading of these files using R, or just convert the data manually. I'm assuming you or your colleagues don't have any access to LabVIEW yourselves otherwise you could just create a LabVIEW tool to do the conversion (and build it as a standalone application or DLL, if you have the professional development system or app builder - you could run the built app from your R code by passing parameters on a command line).
The document on your first link refers to (a) add-ins for OpenOffice Calc and for Excel, which should work for a manual conversion and which you might be able to automate using those programs' respective macro languages, and (b) a C DLL for reading TDMS - would it be possible for you to use one of those?