提取，格式化和分离已存储在数据框列中的JSON

问题描述

我该如何解析和处理已经存在于数据框中的JSON?

How might I parse and process JSON that already lives inside a data frame?

样本数据:

df <- data.frame(
    id = c("x1", "x2"), 
    y = c('[{"Property":"94","Value":"Error"},{"Property":"C1","Value":"Found Match"},{"Property":"C2","Value":"Address Mismatch"}]', '[{"Property":"81","Value":"XYZ"},{"Property":"D1","Value":"Blah Blah"},{"Property":"Z2","Value":"Email Mismatch"}]')
)

我想提取y列中的原始JSON并将其格式化并分离为有序的列，最好使用library(jsonlite).

I want to extract, format and separate the raw JSON in column y into orderly columns, ideally with library(jsonlite).

提前谢谢！

推荐答案

使用jsonlite和tidyverse:

Using jsonlite and the tidyverse:

library(tidyverse)
library(jsonlite)

df %>% mutate(y = map(y, ~fromJSON(as.character(.x)))) %>% unnest()

# Source: local data frame [6 x 3]
# 
#       id Property            Value
#   <fctr>    <chr>            <chr>
# 1     x1       94            Error
# 2     x1       C1      Found Match
# 3     x1       C2 Address Mismatch
# 4     x2       81              XYZ
# 5     x2       D1        Blah Blah
# 6     x2       Z2   Email Mismatch

或不带purrr

df %>% rowwise() %>% mutate(y = list(fromJSON(as.character(y)))) %>% unnest()

，或者仅包含dplyr和jsonlite，

df %>% rowwise() %>% do(data.frame(id = .$id, fromJSON(as.character(.$y))))

或仅具有基数R和jsonlite

do.call(rbind, 
        Map(function(id, y){data.frame(id, fromJSON(as.character(y)))}, 
            df$id, df$y))

所有人都会返回同一件事，所以选择哪个对您来说最有意义.

All return the same thing, so pick which makes the most sense to you.

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