如何在R中解析具有堆叠的多个JSON的文件? [英] How to parse a file with stacked multiple JSONs in R?

问题描述

我在R example1.json中具有以下堆叠的JSON"对象:

I have the following "stacked JSON" object within R, example1.json:

{"ID":"12345","Timestamp":"20140101", "Usefulness":"Yes",
  "Code":[{"event1":"A","result":"1"},…]}
{"ID":"1A35B","Timestamp":"20140102", "Usefulness":"No",
  "Code":[{"event1":"B","result":"1"},…]}
{"ID":"AA356","Timestamp":"20140103", "Usefulness":"No",
  "Code":[{"event1":"B","result":"0"},…]}

这些不是逗号分隔的.基本目标是将某些字段(或所有字段)解析为R data.frame或data.table:

These are not comma-separated. The fundamental goal would be to parse certain fields (or all fields) into an R data.frame or data.table:

    Timestamp    Usefulness
 0   20140101      Yes
 1   20140102      No
 2   20140103      No

通常，我会在R中读取JSON，如下所示:

Normally, I would read in a JSON within R as follows:

library(jsonlite)

jsonfile = "example1.json"
foobar = fromJSON(jsonfile)

但是这会引发解析错误:

This however throws a parsing error:

Error: lexical error: invalid char in json text.
          [{"event1":"A","result":"1"},…]} {"ID":"1A35B","Timestamp"
                     (right here) ------^

这是与以下类似的问题，但在R中:

This is a similar question to the following, but in R: multiple Json objects in one file extract by python

此文件格式称为换行分隔的JSON"，即NDJSON.

This file format is called a "newline delimited JSON", NDJSON.

推荐答案

1. 三个点...使您的JSON无效，因此使您的lexical error无效.

1. The three dots ... invalidate your JSON, hence your lexical error.

您可以使用jsonlite::stream_in()在JSON行中流式传输".

You can use jsonlite::stream_in() to 'stream in' lines of JSON.

---

library(jsonlite)

jsonlite::stream_in(file("~/Desktop/examples1.json"))
# opening file input connection.
# Imported 3 records. Simplifying...
# closing file input connection.
#      ID Timestamp Usefulness Code
# 1 12345  20140101        Yes A, 1
# 2 1A35B  20140102         No B, 1
# 3 AA356  20140103         No B, 0

数据

我已经清理了示例数据以使其成为有效的JSON，并将其另存为~/Desktop/examples1.json

{"ID":"12345","Timestamp":"20140101", "Usefulness":"Yes","Code":[{"event1":"A","result":"1"}]}
{"ID":"1A35B","Timestamp":"20140102", "Usefulness":"No","Code":[{"event1":"B","result":"1"}]}
{"ID":"AA356","Timestamp":"20140103", "Usefulness":"No","Code":[{"event1":"B","result":"0"}]}

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