如何根据R中的条件填充缺少的值

# 均值填充
df$column <- ifelse(is.na(df$column), mean(df$column, na.rm = TRUE), df$column)

# 中位数填充
df$column <- ifelse(is.na(df$column), median(df$column, na.rm = TRUE), df$column)

# 众数填充
mode <- function(x) {
  ux <- unique(x)
  ux[which.max(tabulate(match(x, ux)))]
}
df$column <- ifelse(is.na(df$column), mode(df$column), df$column)

# 线性插值
library(zoo)
df$column <- na.approx(df$column)

# 多项式插值
library.interpolate)
df$column <- polyint(df$column, degree = 2)

# 使用随机森林模型预测缺失值
library(randomForest)
set.seed(123)
rf_model <- randomForest(column ~ ., data = df[!is.na(df$column), ])
df$column[is.na(df$column)] <- predict(rf_model, df[is.na(df$column), ])

# 使用KNN填充
library(DMwR)
df <- knnImputation(df, k = 5)

# 根据某个条件填充
df$column <- ifelse(df$condition_column == "some_value" & is.na(df$column), "filled_value", df$column)