如何确定字符向量是有效的数字还是整数向量 [英] how to determine if a character vector is a valid numeric or integer vector

问题描述

我正在尝试将嵌套列表结构转换为数据框.该列表看起来类似于以下内容(它是使用httr包从解析的JSON中读取的序列化数据).

I am trying to turn a nested list structure into a dataframe. The list looks similar to the following (it is serialized data from parsed JSON read in using the httr package).

  myList <- list(object1 = list(w=1, x=list(y=0.1, z="cat")), object2 = list(w=NULL, x=list(z="dog")))

我的原始示例数据太简单了.实际数据参差不齐，这意味着并非每个对象都存在所有变量，并且某些列表元素为NULL.我编辑了数据以反映这一点.

unlist(myList)在递归地展平列表方面做得很好，然后我可以使用lapply很好地展平所有对象.

unlist(myList) does a great job of recursively flattening the list, and I can then use lapply to flatten all the objects nicely.

  flatList <- lapply(myList, FUN= function(object) {return(as.data.frame(rbind(unlist(object))))}) 

最后，我可以使用plyr::rbind.fill

  myDF <- do.call(plyr::rbind.fill, flatList)
  str(myDF)

  #'data.frame':    2 obs. of  3 variables:
  #$ w  : Factor w/ 2 levels "1","2": 1 2
  #$ x.y: Factor w/ 2 levels "0.1","0.2": 1 2
  #$ x.z: Factor w/ 2 levels "cat","dog": 1 2

问题在于w和x.y现在被解释为字符向量，默认情况下将其解析为数据帧中的因子.我相信unlist()是罪魁祸首，但我想不出另一种方法来递归地平滑列表结构.一种解决方法是对数据框进行后处理，然后分配数据类型.确定向量是有效数字还是整数向量的最佳方法是什么?

The problem is that w and x.y are now being interpreted as character vectors, which by default get parsed as factors in the dataframe. I believe that unlist() is the culprit, but I can't figure out another way to recursively flatten the list structure. A workaround would be to post-process the dataframe, and assign data types then. What is the best way to determine if a vector is a valid numeric or integer vector?

推荐答案

如所讨论的

As discussed here, checking if as.numeric returns NA values is a simple approach to checking if a character string contains numeric data. Now you can do something like:

myDF2 <- lapply(myDF, function(col) {
  if (suppressWarnings(all(!is.na(as.numeric(as.character(col)))))) {
    as.numeric(as.character(col))
  } else {
    col
  }
})
str(myDF2)
# List of 3
#  $ w  : num [1:2] 1 2
#  $ x.y: num [1:2] 0.1 0.2
#  $ x.z: Factor w/ 2 levels "cat","dog": 1 2

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