R：从数据框列中获取 JSON 字符串的向量（逐行）

Question

我想为数据帧的每一行创建一个数据帧列的 JSON 字符串（即获取 Json 字符串向量）。即我想从这段代码中复制这个输出，但使用更高效的代码（因为我的非玩具数据帧的速度非常糟糕）：

apply(mtcars, 1, function(x) jsonlite::toJSON(as.list(x), na = "null", auto_unbox = TRUE))

运行以下代码很快，但我不确定如何操作以获得与上述代码相同的格式。

jsonlite::toJSON(mtcars, dataframe = "rows", pretty=FALSE, na = "null", auto_unbox = TRUE, na = "null")

所需输出示例：

马自达 RX4 "{"mpg":21,"cyl":6,"disp":160,"hp":110,"drat":3.9,"wt":2.62,"qsec":16.46,"vs":0, “上午”：1，“齿轮”：4，“碳水化合物”：4}” > 马自达 RX4 Wag
"{"mpg":21,"cyl":6,"disp":160,"hp":110,"drat":3.9,"wt":2.875,"qsec":17.02,"vs":0, "am":1,"gear":4,"carb":4}"

达特桑 710
"{"mpg":22.8,"cyl":4,"disp":108,"hp":93,"drat":3.85,"wt":2.32,"qsec":18.61,"vs":1, "am":1,"gear":4,"carb":1}"

Answer 1

试试这个

df_to_json_vec <- function(df) {
  # `collapse = FALSE` is the key.
  jsonlite::toJSON(df, dataframe = "rows", na = "null", auto_unbox = TRUE, collapse = FALSE)
}
`names<-`(df_to_json_vec(`row.names<-`(df, NULL)), row.names(df))

性能基准

# create a dataframe ten times the length of mtcars
df <- dplyr::bind_rows(replicate(10, mtcars, simplify = FALSE))
microbenchmark::microbenchmark(
  `names<-`(df_to_json_vec(`row.names<-`(df, NULL)), row.names(df)), 
  apply(df, 1, function(x) jsonlite::toJSON(as.list(x), na = "null", auto_unbox = TRUE)), 
  unit = "ms"
)

结果

Unit: milliseconds
                                                                                                expr      min        lq     mean   median        uq      max neval cld
                           res1 <- `names<-`(df_to_json_vec(`row.names<-`(df, NULL)), row.names(df))   1.3687   1.47295   1.6430   1.5700   1.75415   2.7115   100  a 
 res2 <- apply(df, 1, function(x) jsonlite::toJSON(as.list(x),      na = "null", auto_unbox = TRUE)) 206.9659 223.43650 234.2259 230.8466 241.79225 343.3378   100   b

此外，新代码产生的结果集与旧代码相同。

> all(res1 == res2)
[1] TRUE