Question

我有一个数据帧列表，我已经计算了每个数据帧的每一列的 colmeans，除了数据帧的第 1 列和第 2 列。我的数据框列表的一小部分位于底部。

我用下面的行计算了colmeans

df_colmeans <- lapply(df, function(x) colMeans(x[-c(1:2)],na.rm = T))

我想将 colmeans 添加回我的数据帧列表中的每个数据帧，并尝试了下面的行，但结果不正确。

df <- rbind(df[-c(1:2)],df_colmeans)

我收到以下错误

在 rbind(df[-c(1:2)], df_colmeans) 中：结果的列数不是向量长度的倍数（arg 2）

如果有一种方法可以一步完成，而无需创建单独的变量 (df_colmeans)，那将是理想的。

非常感谢任何帮助和建议。

list(Fe.II. = structure(list(Lab = c("AD", "AD", "AK", "AK", 
"AO", "AO", "BQ", "BQ", "CI", "CI", "CL", "CL", "CP", "CP", "CU", 
"CU", "CW", "CW", "CZ", "CZ", "DA", "DA", "DC", "DC", "DF", "DF", 
"EQ", "EQ", "EY", "EY", "FL", "FL", "FM", "FM", "FO", "FO", "FP", 
"FP", "FR", "FR", "GB", "GB", "GC", "GC", "GL", "GL", "GM", "GM", 
"GT", "GT", "GY", "GZ", "I", "I", "K", "K", "M", "M", "Q", "Q", 
"S", "S", "U", "U", "V", "V", "W", "W"), `Sample Prep` = c(335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 337, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337), `1` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.19, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 0.17, NA, 0.14, NA, NA, NA, NA, NA), `2` = c(NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, 0.01, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.13, NA, 0.15, NA, NA, 
NA, NA, NA), `3` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 0.02, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 0.23, NA, 0.29, NA, NA, NA, NA), `4` = c(NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.02, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.22, NA, 
0.29, NA, NA, NA, NA)), class = "data.frame", row.names = c(NA, 
-68L)), SiO2 = structure(list(Lab = c("AD", "AD", "AK", "AK", 
"AO", "AO", "BQ", "BQ", "CI", "CI", "CL", "CL", "CP", "CP", "CU", 
"CU", "CW", "CW", "CZ", "CZ", "DA", "DA", "DC", "DC", "DF", "DF", 
"EQ", "EQ", "EY", "EY", "FL", "FL", "FM", "FM", "FO", "FO", "FP", 
"FP", "FR", "FR", "GB", "GB", "GC", "GC", "GL", "GL", "GM", "GM", 
"GT", "GT", "GY", "GZ", "I", "I", "K", "K", "M", "M", "Q", "Q", 
"S", "S", "U", "U", "V", "V", "W", "W"), `Sample Prep` = c(335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 337, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337), `1` = c(3.65, NA, 3.595, NA, 3.645, NA, 3.66, NA, 
3.644, NA, 3.547, NA, 3.648, NA, 3.655, NA, NA, NA, 3.666, NA, 
3.686, NA, 3.674, NA, 3.667, NA, 3.59, NA, 3.63, NA, 3.689, NA, 
3.64, NA, 3.58, NA, NA, NA, 3.46, NA, 3.71, NA, 3.66, NA, 3.65, 
NA, 3.64, NA, 3.503, NA, NA, NA, 3.631, NA, 3.731, NA, 3.656, 
NA, NA, NA, 3.75, NA, 3.656, NA, 3.667, NA, 3.684, NA), `2` = c(3.6, 
NA, 3.591, NA, 3.646, NA, 3.65, NA, 3.625, NA, 3.548, NA, 3.648, 
NA, 3.643, NA, NA, NA, 3.679, NA, 3.69, NA, 3.646, NA, 3.577, 
NA, 3.6, NA, 3.63, NA, 3.692, NA, 3.66, NA, 3.59, NA, NA, NA, 
3.512, NA, 3.703, NA, 3.62, NA, 3.63, NA, 3.63, NA, 3.49, NA, 
NA, NA, 3.627, NA, 3.739, NA, 3.669, NA, NA, NA, 3.73, NA, 3.66, 
NA, 3.664, NA, 3.669, NA), `3` = c(NA, 3.55, NA, 3.662, NA, 3.665, 
NA, 3.65, NA, 3.67, NA, 3.576, NA, 3.631, NA, 3.683, NA, NA, 
NA, 3.638, NA, 3.703, NA, 3.666, NA, NA, NA, 3.59, NA, 3.61, 
NA, 3.657, NA, 3.67, NA, NA, NA, NA, NA, 3.8, NA, 3.684, NA, 
3.69, NA, 3.66, NA, 3.69, NA, 4.398, 3.672, NA, NA, 3.678, NA, 
3.769, NA, 3.678, NA, 3.718, NA, 3.75, NA, 3.636, NA, NA, NA, 
3.603), `4` = c(NA, 3.57, NA, 3.69, NA, 3.624, NA, 3.66, NA, 
3.673, NA, 3.551, NA, 3.64, NA, 3.684, NA, NA, NA, 3.678, NA, 
3.673, NA, 3.696, NA, NA, NA, 3.56, NA, 3.62, NA, 3.615, NA, 
3.66, NA, NA, NA, NA, NA, 3.642, NA, 3.684, NA, 3.67, NA, 3.67, 
NA, 3.67, NA, 4.38, 3.672, NA, NA, 3.68, NA, 3.757, NA, 3.673, 
NA, 3.759, NA, 3.78, NA, 3.64, NA, NA, NA, 3.597)), class = "data.frame", row.names = c(NA, 
-68L)), CaO = structure(list(Lab = c("AD", "AD", "AK", "AK", 
"AO", "AO", "BQ", "BQ", "CI", "CI", "CL", "CL", "CP", "CP", "CU", 
"CU", "CW", "CW", "CZ", "CZ", "DA", "DA", "DC", "DC", "DF", "DF", 
"EQ", "EQ", "EY", "EY", "FL", "FL", "FM", "FM", "FO", "FO", "FP", 
"FP", "FR", "FR", "GB", "GB", "GC", "GC", "GL", "GL", "GM", "GM", 
"GT", "GT", "GY", "GZ", "I", "I", "K", "K", "M", "M", "Q", "Q", 
"S", "S", "U", "U", "V", "V", "W", "W"), `Sample Prep` = c(335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 337, 337, 335, 
337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 335, 337, 
335, 337), `1` = c(0.04, NA, NA, NA, 0.055, NA, 0.053, NA, 0.055, 
NA, 0.021, NA, 0.049, NA, 0.052, NA, NA, NA, 0.053, NA, 0.056, 
NA, 0.054, NA, 0.036, NA, 0.032, NA, 0.06, NA, 0.053, NA, 0.05, 
NA, 0.043, NA, NA, NA, NA, NA, 0.054, NA, 0.057, NA, 0.052, NA, 
0.05, NA, 0.048, NA, NA, NA, 0.056, NA, 0.043, NA, 0.053, NA, 
NA, NA, 0.052, NA, 0.076, NA, 0.051, NA, 0.047, NA), `2` = c(0.04, 
NA, NA, NA, 0.054, NA, 0.053, NA, 0.055, NA, 0.023, NA, 0.05, 
NA, 0.05, NA, NA, NA, 0.051, NA, 0.053, NA, 0.056, NA, 0.036, 
NA, 0.032, NA, 0.06, NA, 0.053, NA, 0.05, NA, 0.043, NA, NA, 
NA, NA, NA, 0.056, NA, 0.056, NA, 0.057, NA, 0.05, NA, 0.05, 
NA, NA, NA, 0.053, NA, 0.043, NA, 0.053, NA, NA, NA, 0.052, NA, 
0.076, NA, 0.051, NA, 0.047, NA), `3` = c(NA, 0.04, NA, NA, NA, 
0.055, NA, 0.053, NA, 0.057, NA, 0.023, NA, 0.05, NA, 0.055, 
NA, NA, NA, 0.053, NA, 0.053, NA, 0.054, NA, NA, NA, 0.045, NA, 
0.06, NA, 0.052, NA, 0.05, NA, NA, NA, NA, NA, 0.05, NA, 0.054, 
NA, 0.056, NA, 0.054, NA, 0.05, NA, 0.054, 0.057, NA, NA, 0.057, 
NA, 0.053, NA, 0.054, NA, 0.052, NA, 0.05, NA, 0.045, NA, NA, 
NA, 0.051), `4` = c(NA, 0.04, NA, NA, NA, 0.054, NA, 0.053, NA, 
0.056, NA, 0.019, NA, 0.052, NA, 0.056, NA, NA, NA, 0.051, NA, 
0.051, NA, 0.056, NA, NA, NA, 0.047, NA, 0.06, NA, 0.046, NA, 
0.05, NA, NA, NA, NA, NA, 0.05, NA, 0.054, NA, 0.055, NA, 0.054, 
NA, 0.05, NA, 0.052, 0.056, NA, NA, 0.055, NA, 0.053, NA, 0.053, 
NA, 0.051, NA, 0.052, NA, 0.046, NA, NA, NA, 0.051)), class = "data.frame", row.names = c(NA, 
-68L)))

Answer 1

是否要将列均值作为新行添加到现有数据框中？

试试：

result <- lapply(df, function(x) rbind(x[-c(1:2)], colMeans(x[-c(1:2)],na.rm = TRUE)))

向数据帧列表中的每个数据帧添加一个新行 R

1 个答案: