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r - 在 R 中的列上应用变异

问题描述

我有一些缺失的数据，我试图将它们归结为每列的平均值。我的代码，

apply(train_new, 2, function(x) 
        mutate(
          ifelse(is.na(x) | x < 0, mean(x), x)
        )
)

旨在一举将所有 17 列归为每列的平均值，但这会返回Error during wrapup: no applicable method for 'mutate_' applied to an object of class "c('double', 'numeric')"，并引导我进入调试屏幕。我确定这只是一个语法问题，但我不知道它在哪里。

样本数据：

structure(list(INDEX = c(1, 2, 3, 4, 5, 6), TARGET_WINS = c(39, 
70, 86, 70, 82, 75), TEAM_BATTING_H = c(1445, 1339, 1377, 1387, 
1297, 1279), TEAM_BATTING_2B = c(194, 219, 232, 209, 186, 200
), TEAM_BATTING_3B = c(39, 22, 35, 38, 27, 36), TEAM_BATTING_HR = c(13, 
190, 137, 96, 102, 92), TEAM_BATTING_BB = c(457.7607, 685, 602, 
451, 472, 443), TEAM_BATTING_SO = c(842, 1075, 917, 922, 920, 
973), TEAM_BASERUN_SB = c(97.288, 37, 46, 43, 49, 107), TEAM_BASERUN_CS = c(NA, 
28, 27, 30, 39, 59), TEAM_PITCHING_H = c(NA, 1347, 1377, 1396, 
1297, 1279), TEAM_PITCHING_HR = c(84, 191, 137, 97, 102, 92), 
TEAM_PITCHING_BB = c(530.9595, 689, 602, 454, 472, 443), 
TEAM_PITCHING_SO = c(737.105, 1082, 917, 928, 920, 973), 
TEAM_FIELDING_E = c(NA, 193, 175, 164, 138, 123), TEAM_FIELDING_DP = c(146.234708045, 
155, 153, 156, 168, 149), TEAM_BATTING_1B = c(1199, 908, 
973, 1044, 982, 951)), row.names = c(NA, -6L), class = c("tbl_df", 
"tbl", "data.frame"))

标签： rdplyrapply

解决方案

你可以试试：

library(dplyr)

train_new %>%
  mutate_all(funs(ifelse(is.na(.) | . < 0, mean(., na.rm = T), .)))

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