R语言处理FIFA数据集时如何绘制同列变量图表并排除NA值

解决方案 #

你只需要提前过滤掉原数据中League列为NA的观测即可，修改后代码如下：

# 先过滤掉League列是NA的行，仅保留你需要的12个联赛数据
df_filtered <- df %>% 
  filter(!is.na(League))

# 基于过滤后的数据统计各联赛平均年龄
plotageleague <- df_filtered %>% 
  group_by(League) %>% 
  summarise(age = mean(Age, na.rm = TRUE))

options(repr.plot.width = 12, repr.plot.height = 8)

ggplot()+
  geom_histogram(df_filtered, mapping = aes(Age, fill = League), bins = 15)+
  geom_vline(plotageleague, mapping = aes(xintercept = age), color = "red", size = 1.5)+
  geom_text(plotageleague, mapping = aes(x = age+3, y = 65, label = round(age,digits = 2)))+
  facet_wrap(League~.)+
  theme_minimal()+
  theme(legend.position = "bottom")+
  labs(y = "Frequency", title = "", caption = "")

• 代码中给mean()函数加了na.rm=TRUE参数，避免Age列存在缺失值时平均年龄计算结果为NA
• 可以自行调整geom_histogram的bins参数优化年龄分布的展示效果
• 如果不需要单独存储过滤后的数据集，也可以直接在绘图/统计的数据源位置嵌套filter(!is.na(League))逻辑

内容的提问来源于stack exchange，提问作者Enes Kilic