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library(tidyverse) | |
library(rvest) | |
# Read in the website | |
site <- read_html("https://en.wikipedia.org/wiki/2018_FIFA_World_Cup_squads") | |
# Parse website for player tables | |
players <- site %>% | |
html_table(fill = T) %>% | |
.[1:32] # Keep only the tables related to the 32 teams | |
# Parse website for team names | |
teams <- site %>% | |
html_nodes("h3 .mw-headline") %>% | |
html_text() %>% | |
.[1:32] # keep only the first 32 hits | |
# Parse website for coach names | |
coaches <- site %>% | |
html_nodes("h3+ p") %>% | |
html_text() %>% | |
.[1:32] %>% # Keep only the first 32 hits | |
str_replace_all("Coach: ", "") %>% # Clean up the string | |
str_trim() # remove leading whitespaces | |
# Parse website to figure out in which group the team competes | |
group <- site %>% | |
html_nodes("h2 .mw-headline") %>% | |
html_text() %>% | |
.[1:8] %>% # Keep only the first 8 hits | |
rep(4) %>% # Make the group vector match the team vector | |
sort() | |
# Now that we have all of the tables separatly, let's combine them into one | |
table <- tibble(team = teams, | |
coach = coaches, | |
group = group, | |
player = players) %>% | |
unnest() %>% # The players table was a list, we need to unnest this | |
rename(position = `Pos.`) %>% | |
mutate(position = str_sub(position, 2,3)) %>% # Fix parsing error | |
rename(age = `Date of birth (age)`) %>% | |
mutate(age = as.integer(str_sub(age,-4, -2))) |
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