how to add new R packages in azure machine learning for time series anomaly detection

Question

I am trying to find out time series anomaly detection in which i need to install new R packages. In this i m following https://github.com/business-science/anomalize site. In this i needed to install 2 packages: tidyverse and anomalize.

1. can anyone help me on installing package mentioned above as I am getting

   error "package or namespace load failed for tidyverse"

2. Also while adding zip of tidyverse and anomalize do I need to add any other packages and dependencies in that as I am adding only those 2 packages thinking there r no other dependencies I needed for those 2?

you can see in code that I created R_Package.zip and put tidyverse.zip and anomalize.zip in that that

dataset1 <- maml.mapInputPort(1)
data.set <- data.frame(installed.packages())
#install.packages(“src/R_Package/tidyverse_1.2.1.zip”, lib = “.”, 
                  repos = NULL, verbose = TRUE);
#library(tidyverse, lib.loc=”.”, verbose=TRUE);

install.packages("src/tidyverse.zip",lib=".",repos=NULL,verbose=TRUE)
library(R_package, lib.loc = ".", verbose=TRUE);

install.packages("src/anomalize.zip",lib=".",repos=NULL,verbose=TRUE)
library(R_package, lib.loc = ".", verbose=TRUE);

#success <- library("tidyverse", lib.loc = ".", 
                    logical.return = TRUE, verbose = TRUE)
#library(tidyverse)


maml.mapOutputPort("dataset1");

Answer 1

Regarding the error message, notice that it may take some time for the installed packages to become actually available; quoting from Adding R Packages In Azure ML blog post:

Note: In one instance, we ran into an issue where the package was not loaded into the workspace immediately. We had to wait about half an hour before we could use the package. You may be running into this issue as well if you see a message that looks something like this

and you’ve used the above method to check which packages are in your workspace and the package in question appears on that list. If this is the case, we suggest waiting a bit before running your experiment again.

AFAIK yes, you also need to add the package dependencies; the SO thread Install R Packages in Azure ML contains some useful hints.