for循环中的函数有问题

我已经创建了一组对象：

rs_s = {
rs_s_72 <- regular_season %>% filter(season == 72)
rs_s_73 <- regular_season %>% filter(season == 73)
rs_s_74 <- regular_season %>% filter(season == 74)
rs_s_75 <- regular_season %>% filter(season == 75)
rs_s_76 <- regular_season %>% filter(season == 76)
rs_s_77 <- regular_season %>% filter(season == 77)
rs_s_78 <- regular_season %>% filter(season == 78)
rs_s_79 <- regular_season %>% filter(season == 79)
rs_s_80 <- regular_season %>% filter(season == 80)
rs_s_81 <- regular_season %>% filter(season == 81)
rs_s_82 <- regular_season %>% filter(season == 82)
rs_s_83 <- regular_season %>% filter(season == 83)
rs_s_84 <- regular_season %>% filter(season == 84)
rs_s_85 <- regular_season %>% filter(season == 85)
}

如果有人知道，有人能告诉我哪里出了问题，以及我如何修复它吗

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编辑：我还研究了本网站和其他网站上的其他几个问题，但没有一个问题与这个问题特别相关。

如果我们在全局环境中创建了以“rs_s___”开头的对象，请根据

mget

的模式将这些对象放入

列表中，提取
correct
列，并使用
sapply

sapply(mget(ls(pattern = '^rs_s_\\d+$')), function(x) mean(x$correct))


根据语法，最好使用“季节”进行分组，而不是
筛选
ing，从而避免创建多个对象，然后收集这些对象以计算
平均值

library(dplyr)
regular_season %>%
    group_by(season) %>%
    summarise(Mean = mean(correct, na.rm = TRUE), .groups = 'drop')


如果我们只需要特定“季节”的
平均值
，则在
分组依据

regular_season %>%
   filter(season %in% 72:85) %>%
   group_by(season) %>%
   summarise(Mean = mean(correct, na.rm = TRUE), .groups = 'drop') 

如果我们在全局环境中创建了以“rs_s__”开头的对象，则根据
mget
的模式将这些对象放入
列表
，提取
correct
列，并通过
sapply
在
列表上循环得到
平均值

sapply(mget(ls(pattern = '^rs_s_\\d+$')), function(x) mean(x$correct))


根据语法，最好使用“季节”进行分组，而不是
筛选
ing，从而避免创建多个对象，然后收集这些对象以计算
平均值

library(dplyr)
regular_season %>%
    group_by(season) %>%
    summarise(Mean = mean(correct, na.rm = TRUE), .groups = 'drop')


如果我们只需要特定“季节”的
平均值
，则在
分组依据

regular_season %>%
   filter(season %in% 72:85) %>%
   group_by(season) %>%
   summarise(Mean = mean(correct, na.rm = TRUE), .groups = 'drop') 

嘿@akrun谢谢你的评论-你知道我如何在语法上更好地表达它吗？根据显示的语法，你正在全局环境中创建多个对象。i、 e.
rs_s_72
，
rs_s_73
等。
rs_s={.
没有任何意义。谢谢你的评论-你知道我如何在语法上更好地表达它吗？根据显示的语法，你正在全局环境中创建多个对象。例如，
rs_72
，
rs_73
等等。
rs_s={.
没有意义