根据 r 中另一个 dataframe 的匹配 ID 从 dataframe 中添加最小值

Question

I have two dataframes (Dataframe #1 & #2). The values in columns A & B in the Dataframe #2, are from column ID_1 in the Dataframe #1 and indicates contiguous (ie neighboring) areas of each ID_2 row. That is, the first row of the Dataframe #2 (ie ID_2=7) is neighboring with ID_1= 1 & 2.

What I want to do is the following: If a value of ID_1 can be found in either column A or B in the Dataframe #2, I would like to find the lowest First_year value and add it to the Dataframe #1 as a new column. Please refer to the Dataframe #3 for the table I would like to create. For instance, ID_1=1 is shown in row #1 &4 in the Dataframe #2 and the oldest First_year is 1990.

I would really appreciate it if anyone could help me. Have a great night.

Dataframe #1

ID_1 col1 
1    10 
2    15
3    20
4    10
5    20
6    15

Dataframe #2

ID_2 A B First_year
7    1 2 1990
8    3 4 1991
9    2 3 1995
10   1 3 1992
11   4 5 1990
12   3 4 1999

Dataframe #3

ID_1  oldest_First_year
1        1990
2        1990
3        1991
4        1990
5        1990
6         NA

Answer 1

Perform a join after getting dataframe 2 in long format and get the minimum value of First_year for each ID_1 .

library(dplyr)
library(tidyr)

df1 %>%
  left_join(df2 %>%
            pivot_longer(cols = c(A, B)), by = c('ID_1' = 'value')) %>%
  group_by(ID_1) %>%
  summarise(oldest_first_year = min(First_year))

#   ID_1 oldest_first_year
#  <int>             <int>
#1     1              1990
#2     2              1990
#3     3              1991
#4     4              1990
#5     5              1990
#6     6                NA

data

df1 <- structure(list(ID_1 = 1:6, col1 = c(10L, 15L, 20L, 10L, 20L, 
15L)), class = "data.frame", row.names = c(NA, -6L))

df2 <- structure(list(ID_2 = 7:12, A = c(1L, 3L, 2L, 1L, 4L, 3L), B = c(2L, 
4L, 3L, 3L, 5L, 4L), First_year = c(1990L, 1991L, 1995L, 1992L, 
1990L, 1999L)), class = "data.frame", row.names = c(NA, -6L))