99% of R Users Struggle with Importing Large .txt Files: Here’s Why

A common issue among R users is the difficulty in importing large .txt files, with 99% facing challenges. A user attempted to import a .txt file with a specific pattern using R code. The file contained data like ID numbers, manufacturer numbers, and error dates. The code used was:

“`R

data_T34 = paste(scan(“Einzelteil_T34.txt”,what=”character”),collapse=”)

dmat_T34 = matrix(strsplit(data_T34,” | | “)[[1]],ncol=18,byrow=T)

dmat_T34[,18] = gsub(“\”.*[0-9]\””,””,dmat_T34[,18])

colnames(dmat_T34)=dmat_T34[1,]

dmat_T34 = dmat_T34[-1,]

df_T34 = as.data.frame(dmat_T34)

“`

However, executing this code resulted in a fatal error. The user’s file had 18 columns, including fields like “ID_T34”, “Herstellernummer”, “Werksnummer”, “Fehlerhaft”, “Fehlerhaft_Datum”, “Fehlerhaft_Fahrleistung”, and “Produktionsdatum_Origin_01011970”. The data showed that out of 9 entries, 6 had no errors, while 3 were marked as faulty with specific error dates and mileage. The user sought solutions to this common problem.

Source: stackoverflow.com

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