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Caveat: novice. I have several data.tables with millions of rows each, variables are mostly dates and factors. I was using rbindlist() to combine them because. Yesterday, after breaking up the tables into smaller pieces vertically (instead of the current horizontal splicing), I was trying to understand rbind better (especially with fill = TRUE) and also tried bind_rows() and then tried to verify the results but identical() returned FALSE.
library(data.table)
library(dplyr)
DT1 <- data.table(a=1, b=2)
DT2 <- data.table(a=4, b=3)
DT_bindrows <- bind_rows(DT1,DT2)
DT_rbind <- rbind(DT1,DT2)
identical(DT_bindrows,DT_rbind)
# [1] FALSE
Visually inspecting the results from bind_rows() and rbind() says they are indeed identical. I read this and this (from where I adapted the example). My question: (a) what am I missing, and (b) if the number, names, and order of my columns is the same, should I be concerned that identical() = FALSE?
491
rbind() throws an error whereas bind_rows assigns “NA” to those rows of columns missing in one of the data frames where the value is not provided by the data frames.
We go back to initializing the output data frame with no rows and then adding the result of each turn of the loop as a new row in the output data frame. But when you now use bind_rows() rather than rbind() it runs much, much faster.
To join two data frames (datasets) vertically, use the rbind function. The two data frames must have the same variables, but they do not have to be in the same order. If data frameA has variables that data frameB does not, then either: Delete the extra variables in data frameA or.
The name of the rbind R function stands for row-bind. The rbind function can be used to combine several vectors, matrices and/or data frames by rows.
The identical checks for attributes which are not the same. With all.equal, there is an option not to check the attributes (check.attributes)
all.equal(DT_bindrows, DT_rbind, check.attributes = FALSE)
#[1] TRUE
If we check the str of both the datasets, it becomes clear
str(DT_bindrows)
#Classes ‘data.table’ and 'data.frame': 2 obs. of 2 #variables:
# $ a: num 1 4
# $ b: num 2 3
str(DT_rbind)
#Classes ‘data.table’ and 'data.frame': 2 obs. of 2 #variables:
# $ a: num 1 4
# $ b: num 2 3
# - attr(*, ".internal.selfref")=<externalptr> # reference attribute
By assigning the attribute to NULL, the identical returns TRUE
attr(DT_rbind, ".internal.selfref") <- NULL
identical(DT_bindrows, DT_rbind)
#[1] TRUE
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