R - Use Rbind on Multiple Variables with Similar Names

R - use rbind on multiple variables with similar names

That is the wrong way to handle related items. Better to use a list or dataframe, but you will probably find out why in due course. For now:

do.matrix <- do.call(rbind, lapply( ls(patt="variable"), get) )

Or:

do.matrix <- do.call(rbind, lapply( paste0("variable", 1:10) , get) )

elegant way to use rbind() on multiple dataframes with similar names?

Always try to rigorously capture relations between related instances of data, or related data and methods, or related methods. This generally helps ease aggregate manipulation such as your rbind requirement.

For your case, you should have defined your related data.frames as a single list from the beginning:

foo <- list(data.frame(...), data.frame(...), ... );

And then your requirement could be satisfied thusly:

do.call(rbind, foo );

If it's too late for that, then the solution involving repeated calls to get(), as described in the article to which you linked, can do the job.

R - rbind multiple dataframes in list based on pattern in dataframe name

We can find out which list have "01" in their names using grepl (vals). We then create a new list, one with all vals index together and the other one without them and assign them names.

vals <- grepl("01", names(list_df))
setNames(list(do.call(rbind, list_df[vals]), 
              do.call(rbind, list_df[!vals])), new_list)

How to rbind different data frames with different column names?

Simply use:

colnames(E)=colnames(N1)=colnames(N2)

D <- rbind(E, N1, N2)

Remember that for the rbind to work the dataframes should have the same number of columns.

Aggregate multiple variables with rbind

A dplyr approach would be:

df %>%
  bind_rows(df %>% 
            group_by(year) %>%
            summarize(county = 'Florida', across(starts_with('value'), sum))) %>%
  arrange(year, county)
#>    year         county value1 value2 value3 value4
#> 1  2005 Alachua County      3      3      3      3
#> 2  2005   Baker County      9      9      9      9
#> 3  2005     Bay County      5      5      5      5
#> 4  2005        Florida     17     17     17     17
#> 5  2006 Alachua County      6      6      6      6
#> 6  2006   Baker County      8      8      8      8
#> 7  2006     Bay County      8      8      8      8
#> 8  2006        Florida     22     22     22     22
#> 9  2007 Alachua County      8      8      8      8
#> 10 2007   Baker County      4      4      4      4
#> 11 2007     Bay County     10     10     10     10
#> 12 2007        Florida     22     22     22     22

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