Why does left_join produces NA values-CodePudding

I have these data frames and I want to merge them with left_join, based on the peak column. However, any time that I am trying I am taking NA values

can you help me why?

library(tidyverse)

df1 <- tibble(peak=c("peak1","peak2","peak3"), 
              coord1=c(100,500,1000),
              coord2=c(250,700,1250))

df1
#> # A tibble: 3 × 3
#>   peak  coord1 coord2
#>   <chr>  <dbl>  <dbl>
#> 1 peak1    100    250
#> 2 peak2    500    700
#> 3 peak3   1000   1250

df2 <- tibble(peak=c("peak5","peak6","peak7"), 
              coord1=c(120,280,600),
              coord2=c(300,400,850))
df2
#> # A tibble: 3 × 3
#>   peak  coord1 coord2
#>   <chr>  <dbl>  <dbl>
#> 1 peak5    120    300
#> 2 peak6    280    400
#> 3 peak7    600    850

dplyr::left_join(df1, df2, by="peak")
#> # A tibble: 3 × 5
#>   peak  coord1.x coord2.x coord1.y coord2.y
#>   <chr>    <dbl>    <dbl>    <dbl>    <dbl>
#> 1 peak1      100      250       NA       NA
#> 2 peak2      500      700       NA       NA
#> 3 peak3     1000     1250       NA       NA

^{Created on 2022-12-04 with reprex v2.0.2}

CodePudding user response：

Assuming that your data is the same as the previous question.

data <- list(df1, df2, df3)

> data
[[1]]
# A tibble: 3 × 3
  peak  coord1 coord2
  <chr>  <dbl>  <dbl>
1 peak1    100    250
2 peak2    500    700
3 peak3   1000   1250

[[2]]
# A tibble: 3 × 3
  peak  coord1 coord2
  <chr>  <dbl>  <dbl>
1 peak5    120    300
2 peak6    280    400
3 peak7    900   1850

[[3]]
# A tibble: 3 × 3
  peak   coord1 coord2
  <chr>   <dbl>  <dbl>
1 peak8     900   2000
2 peak9    3000   3400
3 peak10   5600   5850

map(data, ~ .x %>%
      mutate(peak = str_c("peak", 1:nrow(.)))) %>%
  reduce(left_join, by = "peak")

# A tibble: 3 × 7
  peak  coord1.x coord2.x coord1.y coord2.y coord1 coord2
  <chr>    <dbl>    <dbl>    <dbl>    <dbl>  <dbl>  <dbl>
1 peak1      100      250      120      300    900   2000
2 peak2      500      700      280      400   3000   3400
3 peak3     1000     1250      900     1850   5600   5850