Rbind Data Frames Based on a Common Pattern in Data Frame Name

rbind data frames based on a common pattern in data frame name

We can use ls with mget

library(data.table)
rbindlist(mget(ls(pattern = "^df\\.\\d+")))

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Or with dplyr

library(dplyr)
mget(ls(pattern="^df\\.\\d+")) %>%
              bind_rows()

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Or with rbind from base R

do.call(rbind, mget(ls(pattern="^df\\.\\d+")))

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)

using rbind to combine all data sets the names of all data set start with common characters

Try first obtaining a vector of all matching objects using ls() with the pattern ^test:

dfs <- lapply(ls(pattern="^test"), function(x) get(x))
result <- rbindlist(dfs)

I am taking the suggestion by @Rohit to use rbindlist to make our lives easier to rbind together a list of data frames.

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

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

How to bind multiple dataframes in R

If names store the object names of objects created in the global environment, then we need the value of those. We can get those with mget in a list

library(dplyr)
bind_rows(mget(names), .id = 'id')

rbind dataframes with a different column name

You could use rbindlist which takes different column names. Using @LyzandeR's data

library(data.table) #data.table_1.9.5
rbindlist(list(a,b))
#            a         b
# 1: 0.8403348 0.1579255
# 2: 0.4759767 0.8182902
# 3: 0.8091875 0.1080651
# 4: 0.9846333 0.7035959
# 5: 0.2153991 0.8744136
# 6: 0.7604137 0.9753853
# 7: 0.7553924 0.1210260
# 8: 0.7315970 0.6196829
# 9: 0.5619395 0.1120331
#10: 0.5711995 0.7252631

Update

Based on the object names of the 12 datasets (i.e. 'Goal1_Costo', 'Goal2_Costo',..., 'Goal12_Costo'),

 nm1 <- paste(paste0('Goal', 1:12), 'Costo', sep="_")
 #or using `sprintf`
 #nm1 <- sprintf('%s%d_%s', 'Goal', 1:12, 'Costo')
 rbindlist(mget(nm1))

rbind dataframe rows with common IDs

You first get common IDs using intersect and then subset and rbind both dataframes -

valid_ids <- intersect(df1$ID, df2$ID)

rbind(df1[df1$ID %in% valid_ids, ], df2[df2$ID %in% valid_ids, ])

  ID  A  B  C
1  1  0  0  0
2  1  1  0  1
3  1 49 49 32

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