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Alex Rivera
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Suppose that you have a data frame with many rows and many columns. The columns have names. You want to access rows by number, and columns by name. For example, one (possibly slow) way to loop over the rows is for (i in 1:nrow(df)) { print(df[i, "column1"]) # do more things with the data frame... } Another way is to create "lists" for separate columns (like column1_list = df[["column1"] ), and access the lists in one loop. This approach might be fast, but also inconvenient if you want to access many columns. Is there a fast way of looping over the rows of a data frame? Is some other data structure better for looping fast?
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