![]() It sat there for 2 hours before saying it ran out of memory as well Using the ndjson package, which is supposed to be faster and more efficient, but basically the same. The same option but with pagesize = 100k or a million - pretty much the same thing since the problem is the overall memory This works until like 3 million, when it slows down drastically, and gives up at 4 million Using jsonlite's stream_in function to process it. The file is a ndjson file and is a set of yelp reviews from their dataset challenge. Once you locate it, click to select it and then click on the "Import" button at the bottom.So I'm really at my wit's end here, but I have a large dataset that I'm trying to import into R, but my computer takes hours to try and out it in before running out of memory and failing to process it. This will open a window that enables you to browse for the data file you want. Once again, use the "Import Dataset" button in the upper right window in R Studio, but select the third option (From Excel). Importing Data from Excel Spreadsheets (.XLSX files) on a PC or MacĪll of the data sets for PH717 are. Once they save them on their local computer, they have been able to import them into R.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |