R语言dt::datatable顶部过滤器异常：选择'AA'时'A+'行也被筛选出来

问题 #

创建了如下示例数据框：

df2 = data.frame(RTG=c("A+","A+","AA","AA"),CITY=c("A","B","C","D"), stringsAsFactors = T)

随后创建datatable：

datatable(df2, 
          rownames= T,
          colnames = T,
          filter = c('top'),
          extensions = "Buttons", 
          options = list(scrollX = T
                         , lengthChange = T
                         , paging = T    
                         , autoWidth = F
                         , pageLength = T 
                         , dom = 'Blfrtip'
                         , info = T 
                         , searching = F
          ))

使用RTG过滤器选择'AA'时，RTG为'A+'的行也会被显示，不符合预期，请问问题出在哪？

解决方案 #

这是因为datatable默认的顶部筛选（filter='top'）采用的是包含式匹配，而非精确匹配。'A+'字符串里包含'A'，所以会被误匹配出来。同时注意原代码中pageLength = T是错误用法，该参数需设置为数字指定默认每页行数，以下是两种解决办法：

方法1：指定列的精确匹配规则 #

在options的columnDefs中配置目标列的筛选逻辑，关闭正则匹配以实现精确筛选：

datatable(df2, 
          rownames= T,
          colnames = T,
          filter = c('top'),
          extensions = "Buttons", 
          options = list(scrollX = T
                         , lengthChange = T
                         , paging = T    
                         , autoWidth = F
                         , pageLength = 10
                         , dom = 'Blfrtip'
                         , info = T 
                         , searching = F
                         , columnDefs = list(
                             list(targets = 1,  # RTG列的索引（从0开始计数）
                                  type = "string",
                                  search = list(regex = FALSE))
                           )
          ))

方法2：利用因子类型生成精确下拉筛选框 #

由于你已将RTG设为因子类型，可使用filterSelect生成仅包含因子水平的精确下拉选项：

datatable(df2, 
          rownames= T,
          colnames = T,
          extensions = "Buttons", 
          options = list(scrollX = T
                         , lengthChange = T
                         , paging = T    
                         , autoWidth = F
                         , pageLength = 10
                         , dom = 'Blfrtip'
                         , info = T 
                         , searching = F
          )) %>%
  filterSelect(1, "RTG", choices = levels(df2$RTG))

内容的提问来源于stack exchange，提问作者Angelo