Forum Discussion
implementation of R in notebook
- 2 years ago
Anonymous
I found a solution, which I think may be better, but for now it is my contribution in case anyone else facing the same solution has an alternative.
Since you are working as a pipeline to get the data to the lakehouse, change the destination so that it is not a table but a file, that is, files/. After this we can load it with readr and work with tidyverse, here the cumbersome thing is that to take it to tables I had no alternative but to write the files/processed table again, then read with SparkR from there to finally be able to use the write procedure which writes it to tables with overwrite or append mode. It is a longer route than I expected but I hope that if anyone knows a better alternative, let us know through this thread. Thanks to everyone who came to my aid.
Hey jccastelblancos ,
I assume that you have to convert the spark dataframe to a pandas dataframe. Probably this article will help you out on this: fabric-docs/docs/data-science/read-write-pandas.md at main · MicrosoftDocs/fabric-docs · GitHub
Hopefully, ths provides what you are looking for.
Regards,
Tom