CODEWITHSUNDEEP
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user3354212
user3354212

Reputation: 1112

How to merge some columns from a dataframe to another one by a condition

I have two dataframes:df1 and df2

df1=read.table(text="group   co
    A   24952
    A   56826865
    A   56829677
    B   10951
    B   24200
    B   48557215
    B   49537767", header=T, stringsAsFactors=F)

df2=read.table(text="group n1 n2 n3 n4
    A   29671   0   46373   0.02
    B   51236   0   57911   0.1
    A   56483059    121.37  56826203    178.28
    B   48497604    164.98  48531024    164.98", header=T, stringsAsFactors=F)

I would like to merge column 2:5 in df2 to df1 by following conditions:

The result is expected as:

    result=read.table(text="group   co  n1  n2  n3  n4
    A   24952   29671   0   46373   0.02
    A   56826865    56483059    121.37  56826203    178.28
    A   56829677    56483059    121.37  56826203    178.28
    B   10951   51236   0   57911   0.1
    B   24200   51236   0   57911   0.1
    B   48557215    48497604    164.98  48531024    164.98
    B   49537767    48497604    164.98  48531024    164.98", header=T, stringsAsFactors=F)

Thanks for helps.

Upvotes: 0

Views: 193

Answers (1)

rconradin
rconradin

Reputation: 346

Using dplyr:

require(dplyr)

First, I modify the dataframe df2 to know which row is a min row and which is a max row:

df2 %<>% group_by(group) %>% 
    mutate(cond2 = ifelse(n1 == min(n1), "min", ifelse(n3 == max(n3), "max", NA))) %>% 
    ungroup

Then, I join the two dataframes and filter:

df1 %>% left_join(df2, by = "group") %>% 
  group_by(group, co) %>% 
  mutate(cond = ifelse(co < min(n1), "min", ifelse(co > max(n3), "max", NA))) %>% 
  ungroup %>% 
  filter(cond == cond2) %>%
  select(-cond, -cond2)

Which gives the output:

Source: local data frame [7 x 6]

  group       co       n1     n2       n3     n4
1     A    24952    29671   0.00    46373   0.02
2     A 56826865 56483059 121.37 56826203 178.28
3     A 56829677 56483059 121.37 56826203 178.28
4     B    10951    51236   0.00    57911   0.10
5     B    24200    51236   0.00    57911   0.10
6     B 48557215 48497604 164.98 48531024 164.98
7     B 49537767 48497604 164.98 48531024 164.98

Upvotes: 1

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