FULL_JOIN

### Cargar la libreria
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

### Primera tabla
library(readxl)
join_1 <- read_excel("~/Metodos/doc_join/join_1.xlsx") %>%
print()

## # A tibble: 9 × 3
##   CODIGO PRODUCTO Ventas
##   <chr>  <chr>     <dbl>
## 1 C_001  Banana     1000
## 2 C_002  Papaya     1200
## 3 C_003  Camote     1500
## 4 C_004  Maiz       1400
## 5 C_005  Cacao      1800
## 6 C_006  Atun       1600
## 7 C_007  Coco       1500
## 8 C_008  Frijol     1475
## 9 C_009  Sandia     1389

### Segunda tabla
library(readxl)
JOIN_2 <- read_excel("~/Metodos/doc_join/JOIN_2.xlsx") %>%
print()

## # A tibble: 9 × 3
##   CODIGO PRODUCTO CANTIDAD
##   <chr>  <chr>       <dbl>
## 1 C_001  Banana         15
## 2 C_002  Papaya         18
## 3 C_003  Camote         20
## 4 C_004  Maiz           18
## 5 C_005  Cacao          12
## 6 C_006  Atun           46
## 7 C_007  Coco           11
## 8 C_008  Frijol         13
## 9 C_009  Sandia         10

### Combinar las tablas con full_join con los datafrems a utilizar por la variable en comun

Combine<- full_join(join_1, JOIN_2, by= "CODIGO") %>%

### selecciona las variables que se van a mostrar en la tabla

select(CODIGO, PRODUCTO.x, Ventas, CANTIDAD) %>%
print()

## # A tibble: 9 × 4
##   CODIGO PRODUCTO.x Ventas CANTIDAD
##   <chr>  <chr>       <dbl>    <dbl>
## 1 C_001  Banana       1000       15
## 2 C_002  Papaya       1200       18
## 3 C_003  Camote       1500       20
## 4 C_004  Maiz         1400       18
## 5 C_005  Cacao        1800       12
## 6 C_006  Atun         1600       46
## 7 C_007  Coco         1500       11
## 8 C_008  Frijol       1475       13
## 9 C_009  Sandia       1389       10