Using Reduce function to merge recursively [duplicate] - r

Question

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Simultaneously merge multiple data.frames in a list
(9 answers)
Closed 6 years ago.
If I have a list of a list, and the list contains a set of dataframes and I want to merge the dataframes together but don't to merge all the list together. For example
list<- list(list(df1_2010,df2_2010,df3_2010), list(df1_2011,df2_2011,df3_2011), list(df1_2012,df2_2012,df3_2012))
And i want to merge all the 2010 dataframe together by let say column id. And I want to merge the 2011 dataframes together by a similar column id, and I want to merge all the 2012 dataframes together by another similar column id.
I want to output a list of merged dataframes by year:
list(df2010, df2011, df2012)
Here's a schematic of how I want to use the Reduce function:
f<-function(b) merge(...,by="ID",all.x=T)
list<- Reduce(f, list)
But I think this will merge all three lists together instead of each list separately. Let me know your suggestions.

Answer 1

Here's a simple reproducible example that I think maps onto your structure:
n <- 5
set.seed(n)
l <- list( list( data.frame(ID = 1:5, a = rnorm(n)),
data.frame(ID = 1:5, b = rnorm(n)),
data.frame(ID = 1:5, c = rnorm(n)),
data.frame(ID = 1:5, d = rnorm(n)) ),
list( data.frame(ID = 1:5, a = rnorm(n)),
data.frame(ID = 1:5, b = rnorm(n)),
data.frame(ID = 1:5, c = rnorm(n)),
data.frame(ID = 1:5, d = rnorm(n)) ),
list( data.frame(ID = 1:5, a = rnorm(n)),
data.frame(ID = 1:5, b = rnorm(n)),
data.frame(ID = 1:5, c = rnorm(n)),
data.frame(ID = 1:5, d = rnorm(n)) ))
You can write an lapply based function that uses Reduce on each element of the list:
out <-
lapply(l, function(x) Reduce(function(...) merge(..., by="ID", all.x=T), x))
And you should get a list of merged dataframes:
str(out)
List of 3
$ :'data.frame': 5 obs. of 5 variables:
..$ ID: int [1:5] 1 2 3 4 5
..$ a : num [1:5] -0.8409 1.3844 -1.2555 0.0701 1.7114
..$ b : num [1:5] -0.603 -0.472 -0.635 -0.286 0.138
..$ c : num [1:5] 1.228 -0.802 -1.08 -0.158 -1.072
..$ d : num [1:5] -0.139 -0.597 -2.184 0.241 -0.259
$ :'data.frame': 5 obs. of 5 variables:
..$ ID: int [1:5] 1 2 3 4 5
..$ a : num [1:5] 0.901 0.942 1.468 0.707 0.819
..$ b : num [1:5] -0.293 1.419 1.499 -0.657 -0.853
..$ c : num [1:5] 0.316 1.11 2.215 1.217 1.479
..$ d : num [1:5] 0.952 -1.01 -2 -1.762 -0.143
$ :'data.frame': 5 obs. of 5 variables:
..$ ID: int [1:5] 1 2 3 4 5
..$ a : num [1:5] 1.5501 -0.8024 -0.0746 1.8957 -0.4566
..$ b : num [1:5] 0.5622 -0.887 -0.4602 -0.7243 -0.0692
..$ c : num [1:5] 1.463 0.188 1.022 -0.592 -0.112
..$ d : num [1:5] -0.925 0.7533 -0.1126 -0.0641 0.2333

Answer 2

Another way to perform the recursive merge would be to use join_all from library(plyr)
library(plyr)
out1 <- lapply(l, join_all, by="ID") #using the example dataset of #Thomas
identical(out, out1)
# [1] TRUE