Now that we understand the data, we can continue with this particular statistical example.
First, the data scientist will need to load the data into an R data frame object. This example is calling it german_raw.
# --- load the data german_raw<- read.table("german.data", quote = "\"")
The next step is to provide column names that match our data schema table, shown in the preceding:
names(german_raw) <- c("checking", "duration", "creditHistory",
"purpose", "credit", "savings", "employment", "installmentRate",
"personal", "debtors", "presentResidence", "property", "age",
"otherPlans", "housing", "existingBankCredits", "job",
"...