在R DataFrame中基于国别列筛选提取意大利球队

Got it, let's work through this. You need to pull all teams that are from Italy (marked by "ITA" in either hcountry or vcountry). Here are a couple of straightforward ways to do this in R:

Option 1: Using Tidyverse (dplyr + tidyr) #

This method is great if you're already working with tibbles and prefer a pipe-based workflow:

library(dplyr)
library(tidyr)
library(stringr) # Optional, for case standardization

# Extract and clean the Italian teams
italian_teams <- df %>%
  # Reshape data to get one team per row
  pivot_longer(
    cols = c(home, visitor),
    names_to = "team_role",
    values_to = "team_name",
    names_pattern = "(home|visitor)"
  ) %>%
  # Match each team to its country
  mutate(team_country = case_when(
    team_role == "home" ~ hcountry,
    team_role == "visitor" ~ vcountry
  )) %>%
  # Keep only Italian teams
  filter(team_country == "ITA") %>%
  # Optional: Standardize case (fixes "Milan" vs "MILAN")
  mutate(team_name = str_to_title(team_name)) %>%
  # Pull just the team names as a vector
  pull(team_name)

# View the result
italian_teams

Running this will give you:

[1] "Milan"   "Milan"   "Juventus"

Option 2: Base R (No Extra Packages) #

If you prefer sticking to base R, this simple approach works too:

# Get home teams from Italy
home_italian <- df$home[df$hcountry == "ITA"]
# Get visitor teams from Italy
visitor_italian <- df$visitor[df$vcountry == "ITA"]
# Combine into a single vector
italian_teams <- c(home_italian, visitor_italian)

# Optional: Standardize case
italian_teams <- stringr::str_to_title(italian_teams) # Or use tolower()/toupper()

italian_teams

Both methods will get you the list of Italian teams you need. The tidyverse approach is more flexible if you want to do additional data cleaning or manipulation later!

内容的提问来源于stack exchange，提问作者joe borg