Lesson 2

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.3     ✓ purrr   0.3.4
## ✓ tibble  3.1.2     ✓ dplyr   1.0.6
## ✓ tidyr   1.1.3     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(rio)
library(here)

## here() starts at /work/tutorial

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:rio':
## 
##     export

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

## toupper sqrt plot are base functions (always loaded in R)
## most functions are not preloaded. They comes from libraries (packages)

raw_data <- import(here::here("data/food_meat_data.xlsx"))

## New names:
## * `` -> ...16

tibble_data <- as_tibble(raw_data)
smaller_data <- select(tibble_data, country, beef_cons)


## pipe operator 
## the pipe operator will take the output of the last function and pass it to the next function
## makes it easier to write a chain of functions
## AND THEN
## control + shift + M

my_plot <- 
  import(here::here("data/food_meat_data.xlsx")) %>%
  as_tibble() %>%
  select(country, beef_cons) %>%
  mutate(beef_cons = as.numeric(beef_cons)) %>%
  arrange(-beef_cons) %>%
  ## factor column is an arranged character column
  mutate(country = fct_reorder(country, beef_cons)) %>% 
  head(30) %>% 
  ggplot() +
  geom_col(aes(x = beef_cons, y = country), fill = "dodgerblue2") + 
  geom_label(aes(x = beef_cons + 3, y = country, label = beef_cons), size =2) +
  labs(title = "Top 30 countries for beef consumption", 
       subtitle = "Kg of beef consumed per person per year", 
       caption = "Data source: FAO and nu3",
       y = "", 
       x = "kg/person/year") + 
  ggthemes::theme_wsj() + 
  theme(plot.title = element_text(size = 14), 
        plot.subtitle = element_text(size = 10), 
        plot.caption = element_text(size = 7))

## New names:
## * `` -> ...16

ggplotly(my_plot)

## Warning in geom2trace.default(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabel() has yet to be implemented in plotly.
##   If you'd like to see this geom implemented,
##   Please open an issue with your example code at
##   https://github.com/ropensci/plotly/issues