如何在 R 中左加入并将值重复加入多个变量？

Question

I'm confusing something here, either this isn't the right approach or I'm missing a part of the left_join:

I'm looking to join the "gdp" column, by country and by year, and repeat the value across all three "gender" categories, in a way that all three genders for the same year will have the same associated gdp.

Here's what I have now:

library(tidyverse)

table_1 <- tribble(~"Region",~"Country",~"Year", ~"Gender", ~"median_rate",
 "Central and Southern Asia", "Afghanistan",  2011, "female",       0.186,
"Central and Southern Asia","Afghanistan",  2011, "male",         0.454,
 "Central and Southern Asia", "Afghanistan",  2011, "total",        0.274,
 "Central and Southern Asia", "Afghanistan",  2018, "female",       0.221,
 "Central and Southern Asia", "Afghanistan" , 2018, "male",         0.504,
 "Central and Southern Asia", "Afghanistan",  2018, "total",        0.367)

table_2 <- tribble(~"Country",    ~"gdp", ~"Year",
 "Afghanistan",  551.,  2010,
 "Afghanistan", 599.,2011,
 "Afghanistan",  649.,  2012,
 "Afghanistan",  648.,  2013,
 "Afghanistan",  625.,  2014,
 "Afghanistan",  590.,  2015,
 "Afghanistan",  550.,  2016,
 "Afghanistan",  550.,  2017)

table_1 %>% left_join(table_2, by = "Country")

# A tibble: 48 x 7
   Region                    Country     Year.x Gender median_rate   gdp Year.y
   <chr>                     <chr>        <dbl> <chr>        <dbl> <dbl>  <dbl>
 1 Central and Southern Asia Afghanistan   2011 female       0.186   551   2010
 2 Central and Southern Asia Afghanistan   2011 female       0.186   599   2011
 3 Central and Southern Asia Afghanistan   2011 female       0.186   649   2012
 4 Central and Southern Asia Afghanistan   2011 female       0.186   648   2013
 5 Central and Southern Asia Afghanistan   2011 female       0.186   625   2014
 6 Central and Southern Asia Afghanistan   2011 female       0.186   590   2015
 7 Central and Southern Asia Afghanistan   2011 female       0.186   550   2016
 8 Central and Southern Asia Afghanistan   2011 female       0.186   550   2017
 9 Central and Southern Asia Afghanistan   2011 male         0.454   551   2010
10 Central and Southern Asia Afghanistan   2011 male         0.454   599   2011
# ... with 38 more rows

Expected output would be something like this, with the gdp column from table 2 joined, but only for each matching year, (eg in table 1 there is only data from 2011 and 2018, so it should only match these years)

tribble(~"Region",~"Country",~"Year", ~"Gender", ~"median_rate",~"gdp",
        "Central and Southern Asia", "Afghanistan",  2011, "female",0.186, 550,
        "Central and Southern Asia","Afghanistan",  2011, "male",0.454,550,
        "Central and Southern Asia", "Afghanistan",  2011, "total",0.274,550,
        "Central and Southern Asia", "Afghanistan",  2018, "female", 0.221,590,
        "Central and Southern Asia", "Afghanistan" , 2018, "male",         0.504, 590,
        "Central and Southern Asia", "Afghanistan",  2018, "total",        0.367, 590)

Thanks for your help,

Answer 1

dplyr 's join verbs' by= argument can accept more than one column:

table_1 <- tribble(~"Region",~"Country",~"Year", ~"Gender", ~"median_rate",
 "Central and Southern Asia", "Afghanistan",  2011, "female",       0.186,
 "Central and Southern Asia","Afghanistan",  2011, "male",         0.454,
 "Central and Southern Asia", "Afghanistan",  2011, "total",        0.274,
 "Central and Southern Asia", "Afghanistan",  2018, "female",       0.221,
 "Central and Southern Asia", "Afghanistan" , 2018, "male",         0.504,
 "Central and Southern Asia", "Afghanistan",  2018, "total",        0.367)

table_2 <- tribble(~"Country",    ~"gdp", ~"Year",
 "Afghanistan",  551.,  2010,
 "Afghanistan", 599.,2011,
 "Afghanistan",  649.,  2012,
 "Afghanistan",  648.,  2013,
 "Afghanistan",  625.,  2014,
 "Afghanistan",  590.,  2015,
 "Afghanistan",  550.,  2016,
 "Afghanistan",  550.,  2017)

table_1 %>% left_join(table_2, by = c("Country", "Year"))
# # A tibble: 6 x 6
#   Region                    Country      Year Gender median_rate   gdp
#   <chr>                     <chr>       <dbl> <chr>        <dbl> <dbl>
# 1 Central and Southern Asia Afghanistan  2011 female       0.186   599
# 2 Central and Southern Asia Afghanistan  2011 male         0.454   599
# 3 Central and Southern Asia Afghanistan  2011 total        0.274   599
# 4 Central and Southern Asia Afghanistan  2018 female       0.221    NA
# 5 Central and Southern Asia Afghanistan  2018 male         0.504    NA
# 6 Central and Southern Asia Afghanistan  2018 total        0.367    NA

Answer 2

We can also use merge from base R

merge(table_1, table_2, by = c("Country", "Year"), all.x = TRUE)
#      Country Year                    Region Gender median_rate gdp
#1 Afghanistan 2011 Central and Southern Asia female       0.186 599
#2 Afghanistan 2011 Central and Southern Asia   male       0.454 599
#3 Afghanistan 2011 Central and Southern Asia  total       0.274 599
#4 Afghanistan 2018 Central and Southern Asia female       0.221  NA
#5 Afghanistan 2018 Central and Southern Asia   male       0.504  NA
#6 Afghanistan 2018 Central and Southern Asia  total       0.367  NA