位置= barplot中的geom_col中的道奇

Question

这是一个足球运动员的数据集，我需要可视化在一个酒吧情节中每个国家 /地区玩游戏数量旁边收到的黄牌总数。因此，我需要计算黄牌的总数和每个联盟国家的游戏总数，并将数据纳入长期格式。

    dput(head(new_soccer_referee))
structure(list(playerShort = c("lucas-wilchez", "john-utaka", 
"abdon-prats", "pablo-mari", "ruben-pena", "aaron-hughes"), player = c("Lucas Wilchez", 
"John Utaka", " Abdón Prats", " Pablo Marí", " Rubén Peña", "Aaron Hughes"
), club = c("Real Zaragoza", "Montpellier HSC", "RCD Mallorca", 
"RCD Mallorca", "Real Valladolid", "Fulham FC"), leagueCountry = c("Spain", 
"France", "Spain", "Spain", "Spain", "England"), birthday = structure(c(4990, 
4390, 8386, 8643, 7868, 3598), class = "Date"), height = c(177L, 
179L, 181L, 191L, 172L, 182L), weight = c(72L, 82L, 79L, 87L, 
70L, 71L), position = c("Attacking Midfielder", "Right Winger", 
NA, "Center Back", "Right Midfielder", "Center Back"), games = c(1L, 
1L, 1L, 1L, 1L, 1L), victories = c(0L, 0L, 0L, 1L, 1L, 0L), ties = c(0L, 
0L, 1L, 0L, 0L, 0L), defeats = c(1L, 1L, 0L, 0L, 0L, 1L), goals = c(0L, 
0L, 0L, 0L, 0L, 0L), yellowCards = c(0L, 1L, 1L, 0L, 0L, 0L), 
    yellowReds = c(0L, 0L, 0L, 0L, 0L, 0L), redCards = c(0L, 
    0L, 0L, 0L, 0L, 0L), photoID = c("95212.jpg", "1663.jpg", 
    NA, NA, NA, "3868.jpg"), rater1 = c(0.25, 0.75, NA, NA, NA, 
    0.25), rater2 = c(0.5, 0.75, NA, NA, NA, 0), refNum = c(1L, 
    2L, 3L, 3L, 3L, 4L), refCountry = c(1L, 2L, 3L, 3L, 3L, 4L
    ), Alpha_3 = c("GRC", "ZMB", "ESP", "ESP", "ESP", "LUX"), 
    meanIAT = c(0.326391469021736, 0.203374724564378, 0.369893594187172, 
    0.369893594187172, 0.369893594187172, 0.325185154120009), 
    nIAT = c(712L, 40L, 1785L, 1785L, 1785L, 127L), seIAT = c(0.000564112354334542, 
    0.0108748941063986, 0.000229489640866464, 0.000229489640866464, 
    0.000229489640866464, 0.00329680952361961), meanExp = c(0.396, 
    -0.204081632653061, 0.588297311544544, 0.588297311544544, 
    0.588297311544544, 0.538461538461538), nExp = c(750L, 49L, 
    1897L, 1897L, 1897L, 130L), seExp = c(0.0026964901062936, 
    0.0615044043187379, 0.00100164730649311, 0.00100164730649311, 
    0.00100164730649311, 0.013752210497518), BMI = c(22.98190175237, 
    25.5922099809619, 24.1140380330271, 23.8480304816206, 23.6614386154678, 
    21.4346093466973), position_new = c("Offense", "Offense", 
    "Goalkeeper", "Defense", "Midfield", "Defense"), rater_mean = c(0.375, 
    0.75, NA, NA, NA, 0.125), ageinyear = c(28, 30, 19, 18, 20, 
    32), ageinyears = c(28, 30, 19, 18, 20, 32)), row.names = c(NA, 
6L), class = "data.frame")

使用数据绘制具有以下特征的条形图：

- X轴显示联盟国家 /地区，而Y轴则显示游戏的数量和纸牌数

- 对于每个国家 /地区，彼此相邻两个酒吧：一款玩游戏的一个，一个用于收到的卡

barplot＆lt; - ggplot（new_soccer_referee，aes（x = leaguecountry，y = number））

barplot + 

geom_bar(fill=c("games","yellowCards")) +

geom_col(Position="dodge") +
  labels(x="leagueCountry", y="number")

ggplot

`

我知道这很混乱，但是我真的很困惑如何用GGPLOT建立层以及如何制定长时间的格式，谁能提供帮助？

Answer 1

一个选项是首先汇总数据以计算Yellowcards和GAMES by leagueCountry的数量。之后，您可以将长时间转换为长时间，从而可以轻松地通过ggplot2绘制。

使用一些虚假的随机示例数据模仿您的真实数据：

set.seed(123)

new_soccer_referee <- data.frame(
  player = sample(letters, 20),
  leagueCountry = sample(c("Spain", "France", "England", "Italy"), 20, replace = TRUE),
  yellowCards = sample(1:5, 20, replace = TRUE),
  games = sample(1:20, 20, replace = TRUE)
)

library(dplyr)
library(tidyr)
library(ggplot2)

new_soccer_referee_long <- new_soccer_referee %>% 
  group_by(leagueCountry) %>%
  summarise(across(c(yellowCards, games), sum)) %>%
  pivot_longer(-leagueCountry, names_to = "variable", values_to = "number")

ggplot(new_soccer_referee_long, aes(leagueCountry, number, fill = variable)) +
  geom_col(position = "dodge")

Answer 2

像这样：

library(tidyverse)

new_soccer_referee %>% 
  select(leagueCountry, games, yellowCards) %>% 
  group_by(leagueCountry) %>% 
  summarise(games = sum(games),
            yellowCars = sum(yellowCards)
            ) %>% 
  pivot_longer(-leagueCountry) %>% 
  ggplot(aes(x=leagueCountry, fill=name, y=value)) +
  geom_col(position = position_dodge())