将 JSON 数组转换为 r 列

Question

关于如何将 JSON 数据转换为 R，我有一个非常具体的问题。 我正在处理来自反应时间测试的数据。 数据包含一些关于 id、gender 和 age 的基本格式，格式为 csv。 但是，反应任务的数据以 JSON 数组的形式提供，具有以下结构：[“刺激 1”、“刺激 2”、选择的答案、反应时间]。

这是数据外观的示例，只是为了让您了解它的基本概念（除了 JSON 数组实际上在原始数据中要长得多）

id     gender   age    reaction_task

HU3    male     34     [["prime1", "target2", 1, 1560], ["prime7", "target6", 2, 1302], ["prime4", "target5", 2, 996]]

我是 R 的新手，并正在寻找一种方法将此 JSON 数组转换为多个 R 列 - 例如像这样：

trial1_stimulus1     trial1_stimulus2   trial1_answer     trial1_time     trail2_stimulus1    trial2_stimulus2    etc

prime1               target2            1                 1560             prime7              target2

我发现了如何使用以下命令将数据与另一个数据分开：

df <- cbind(df, read.table(text = as.character(df$reaction_task), sep = ",", fill=TRUE) )

它有效，但结果非常费力，因为我仍然不得不手动从数据中删除[] 。 所以我想知道是否有更顺畅的方法来处理这项任务？

我也在尝试以下代码，但收到错误消息：

purrr::map_dfr(sosci$A101oRAW, jsonlite::fromJSON)
Fehler: parse error: premature EOF
                                       
                     (right here) ------^

谢谢你的帮助！

编辑：非常感谢 Maydin 提供的答案，它适用于示例数据，但是当数据框包含多个人时：我收到与以前几乎相同的错误警告：

id <- c("HU3", "AB0", "IO9")
gender <- c("male", "female", "male")
age <-c(34, 87, 23)
task <- c("[[\"prime1\", \"target2\", 2, 1529], [\"prime7\", \"target6\", 2, 829], [\"prime4\", \"target5\", 1, 1872]]", "[[\"prime1\", \"target2\", 1, 1560], [\"prime7\", \"target6\", 2, 1302], [\"prime4\", \"target5\", 2, 996]]","[[\"prime1\", \"target2\", 1, 679], [\"prime7\", \"target6\", 1, 2090], [\"prime4\", \"target5\", 1, 528]]")
                                                                                                                                                                                                                                                                                                                                                                                                                 
df <- data.frame(id, gender, age, task)

library(jsonlite)
library(dplyr)

df2 <- data.frame(df[,1:3],fromJSON(as.character(df[,"task"])))
parse error: trailing garbage
          rime4", "target5", 1, 1872]] [["prime1", "target2", 1, 1560]
                     (right here) ------^

Answer 1

library(jsonlite)

df2 <- lapply(1:nrow(df), function(x) {

     data.frame(df[x,1:3],fromJSON(as.character(df[x,"task"])),
        row.names = NULL) })

df2 <- do.call(rbind,df2)

df2

    
   id gender age     X1      X2 X3   X4
1 HU3   male  34 prime1 target2  2 1529
2 HU3   male  34 prime7 target6  2  829
3 HU3   male  34 prime4 target5  1 1872
4 AB0 female  87 prime1 target2  1 1560
5 AB0 female  87 prime7 target6  2 1302
6 AB0 female  87 prime4 target5  2  996
7 IO9   male  23 prime1 target2  1  679
8 IO9   male  23 prime7 target6  1 2090
9 IO9   male  23 prime4 target5  1  528

我认为上面的 output 格式更好，但是如果您想将其转换为列，

library(tidyr)

pivot_wider(data = df2, 
            id_cols = c("id","gender","age"), 
            names_from = c("X1","X2","X3","X4"), 
            values_from =c("X1","X2","X3","X4")) %>% as.data.frame()

如果以后需要，可以使用colnames()等更改列的名称。

数据：

df <- structure(list(id = structure(1L, .Label = "HU3", class = "factor"), 
    gender = structure(1L, .Label = "male", class = "factor"), 
    age = structure(1L, .Label = "34", class = "factor"), reaction_task = structure(1L, .Label = "[[\"prime1\", \"target2\", 1, 1560], [\"prime7\", \"target6\", 2, 1302], [\"prime4\", \"target5\", 2, 996]]", class = "factor")), class = "data.frame", row.names = c(NA, 
-1L))