Combine two data frames by rows (rbind) when they have different sets of columns

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Is it possible to row bind two data frames that don't have the same set of columns? I am hoping to retain the columns that do not match after the bind.

rbind.fill from the package plyr might be what you are looking for.

Combining dataframes when the columns don't match, For example, I was trying to combine data from two different regions into If you try and do this using rbind , you get an error but going through and Of course, you won't actually have any data for these additional columns, so we simply set the Randomly deleting duplicate rows from a dataframeIn "R". Combine two data frames with different number of rows in R [duplicate] Combine two data frames by rows (rbind) when they have different sets of columns. 498.

A more recent solution is to use dplyr's bind_rows function which I assume is more efficient than smartbind.

df1 <- data.frame(a = c(1:5), b = c(6:10))
df2 <- data.frame(a = c(11:15), b = c(16:20), c = LETTERS[1:5])
dplyr::bind_rows(df1, df2)
    a  b    c
1   1  6 <NA>
2   2  7 <NA>
3   3  8 <NA>
4   4  9 <NA>
5   5 10 <NA>
6  11 16    A
7  12 17    B
8  13 18    C
9  14 19    D
10 15 20    E

Efficiently bind multiple data frames by row and column, Install plyr package if you don't have it, and then use rbind.fill : df4 <- rbind(df2, df3[, names(df2)]). If columns in df1 is a subset of those in df2  cbind different length of data frames based on column [duplicate] Combine two data frames by rows (rbind) when they have different sets of columns. Related.

You can use smartbind from the gtools package.

Example:

library(gtools)
df1 <- data.frame(a = c(1:5), b = c(6:10))
df2 <- data.frame(a = c(11:15), b = c(16:20), c = LETTERS[1:5])
smartbind(df1, df2)
# result
     a  b    c
1.1  1  6 <NA>
1.2  2  7 <NA>
1.3  3  8 <NA>
1.4  4  9 <NA>
1.5  5 10 <NA>
2.1 11 16    A
2.2 12 17    B
2.3 13 18    C
2.4 14 19    D
2.5 15 20    E

R Merge - How To Merge Two R Data Frames, When column-binding, rows are matched by position, so all data frames must To match by value, not position, see join. rbind_list() and rbind_all() have been deprecated. You can supply data frames as arguments: bind_rows(one, two). Using rbind() to merge two R data frames. We’ve encountered rbind() before, when appending rows to a data frame. This function stacks the two data frames on top of each other, appending the second data frame to the first. For this function to operate, both data frames need to have the same number of columns and the same column names.

If the columns in df1 is a subset of those in df2 (by column names):

df3 <- rbind(df1, df2[, names(df1)])

Union Multiple Data.Frames with Different Column Names, We're going to walk through how to merge two data frames in R. cbind() – combining the columns of two data frames side-by-side; rbind() – stacking two data joins to handle missing values, and merge using fields with different row names. perhaps based on a daily analysis of what the chicks are fed, you could set up  Data frames to combine. Each argument can either be a data frame, a list that could be a data frame, or a list of data frames. When row-binding, columns are matched by name, and any missing columns will be filled with NA. When column-binding, rows are matched by position, so all data frames must have the same number of rows.

An alternative with data.table:

library(data.table)
df1 = data.frame(a = c(1:5), b = c(6:10))
df2 = data.frame(a = c(11:15), b = c(16:20), c = LETTERS[1:5])
rbindlist(list(df1, df2), fill = TRUE)

rbind will also work in data.table as long as the objects are converted to data.table objects, so

rbind(setDT(df1), setDT(df2), fill=TRUE)

will also work in this situation. This can be preferable when you have a couple of data.tables and don't want to construct a list.

Data Wrangling in R: Combining, Merging and Reshaping Data, Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. (https://stackoverflow.com/questions/3402371/combine-two-data-​frames-by-rows-rbind-when-they-have-different-sets-of-columns)  The first part, do.call(rbind, dfs) binds the rows of data frames into a single data frame. The vapply(dfs, nrow, numeric(1)) finds how many rows each data frame has which is passed to rep in rep(names(dfs), vapply(dfs, nrow, numeric(1))) to repeat the name of the data frame once for each row of the data frame. cbind puts them all together.

How do you rbind two data frames with a different number of , Rda") # Sometimes we have multiple data frames we want to combine. That's because rbind() has a logical argument called # "make.row.names" that match between the two data sets), and "by.x" and "by.y" are also # columns to merge In other words, you don't have to use the by argument if your data # frames have​  I have two data frames with different number of columns and rows. I want to combine them into one data frame. > month.saf Name NCDC Year Month Day HrMn Temp Q 244 AP 99999 2

Merging Data, This is a pure R question, but here we go: use tidyverse packages library(dplyr) library(tibble) res <- df1 %>% rownames_to_column('rnames')  I have two lists named h and g.They each contain 244 dataframes and they look like the following: h[[1]] year avg hr sal 1 2010 0.300 31 2000 2 2011 0.290 30 4000 3 2012 0.275 14 600 4 2013 0.280 24 800 5 2014 0.295 18 1000 6 2015 0.330 26 7000 7 2016 0.315 40 9000 g[[1]] year pos fld 1 2010 A 0.990 2 2011 B 0.995 3 2013 C 0.970 4 2014 B 0.980 5 2015 D 0.990

smartbind: Efficient rbind of data frames, even if the column names , Adding Rows. To join two data frames (datasets) vertically, use the rbind function. The two data frames must have the same variables, but they do  Continuing our discussion on how to merge data frames in R, our attention turns to rbind – the row bind function. Rbind can be used to append two dataframes with the same number of columns together. We will build on the example we started with cbind, the column bind function. At the end of that session, we had a lovely dataframe which

Comments
  • rbind.fill and bind_rows() both silently drop rownames.
  • @MERose Hadley: "Yes, all dplyr methods ignore rownames."
  • Here is a link to documentation: rdocumentation.org/packages/plyr/versions/1.8.4/topics/…
  • I tried smartbind with two large data frames (in total roughly 3*10^6 rows) and aborted it after 10 minutes.
  • A lot has happened in 9 years :) I might not use smartbind today. Note also that the original question did not specify large data frames.
  • This is the most simple, out-of-the-box solution that easily generalizes to any number of dataframes, since you can store them all in separate list elements. Other answers, like the intersect approach, only work for 2 dataframes and don't easily generalize.
  • using dplyr::bind_rows(x, y) in place of rbind(x,y) keeps the column order based on the first data frame.