How can i make arules.apriori work in python using rpy2

Question

I'm trying to run an apriori algorithm in python using rpy2. i've hit a wall because I want to give the algorithm some parameters but than the code doesn't work. if I leave the parameter blank it runs. Is there a way to make the apriori algorithm work with paramters?

I've got some R experience and in R my code would look something like this.

output <- apriori(input, parameter = list(support=.01, confidence=.01, minlen=2))

python code:

from rpy2.robjects.packages import importr
import rpy2.robjects as robjects
import rpy2.robjects.packages as rpackages

# import R packages
base = importr('base')
arules = importr('arules')
arulesViz = importr('arulesViz')
Matrix = importr('Matrix')
utils = importr('utils')
grid = importr('grid')

data = robjects.r('read.transactions("input_data.csv", sep = ",",rm.duplicates=FALSE)')
summary_r = arules.itemFrequency(data, type="absolute")
apr = arules.apriori(data,parameter=list(support=0.001, confidence=0.001, minlen=2))

print(apr)

Answer 1

I've found the answer to the question above on a different forum.

you need to add the following code

from rpy2.robjects.vectors import ListVector

apr = arules.apriori(data,parameter= robjects.ListVector({"support":0.01, "confidence":0.01, "minlen":2}))