CODEWITHSUNDEEP
r
Learner
Learner

Reputation: 757

how to combine several data frame without losing data in one data frame

I can combine two data 

df1 <- read.table(text="info   var1m pos_var1
1       C001        NA       NA
2       C002        NA       NA
3       C003 0.1790000        1
4       C004        NA       NA
5       C007 0.0645000        1
6       C010 0.3895000        1
11      C016 0.2805000        1
12      C017 0.7805001        1", header=T, stringsAsFactors=F)
and this

df2 <- read.table(text="info   var1  var2
1      C003 0.1790 1.1305
2      C007 0.0645 0.2985
3      C010 0.3895 0.1705
4      C016 0.1740 0.3980
5      C017 0.4840 0.3375
6      C022 0.1740 0.3980
7      C023 0.4840 0.3375", header=T, stringsAsFactors=F)

df3 <- read.table(text="info   var1  var2
5      C017 0.4840 0.3375
6      C022 0.1740 0.3980
7      C023 0.4840 0.3375", header=T, stringsAsFactors=F)

I just give an example of three data sets that I am trying to combine. I should not combine them two by two because then I lose some info

for example in order to combine two of them I can do the following 

mydf <- inner_join(df1,df2,'info')

then combine the third , fourth etc dataset into that. However, if I don't have mutual data in df1,df2 and combine , it will be discarded but it might have similar data in df1 and df3.

Is there a way that I combine as many data as I have without losing info but keep all mutual info across all data ?

Upvotes: 1

Views: 44

Answers (1)

Jon Spring
Jon Spring

Reputation: 66765

library(dplyr)
mydf <- df1 %>%
  full_join(df2) %>%
  full_join(df3)

Output:

> mydf
   info     var1m pos_var1   var1   var2
1  C001        NA       NA     NA     NA
2  C002        NA       NA     NA     NA
3  C003 0.1790000        1 0.1790 1.1305
4  C004        NA       NA     NA     NA
5  C007 0.0645000        1 0.0645 0.2985
6  C010 0.3895000        1 0.3895 0.1705
7  C016 0.2805000        1 0.1740 0.3980
8  C017 0.7805001        1 0.4840 0.3375
9  C022        NA       NA 0.1740 0.3980
10 C023        NA       NA 0.4840 0.3375

Upvotes: 1

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