r - 展平深度嵌套且格式错误的 JSON 文件

Question

我使用 tweepy 提取了一些 Twitter 数据，我从那里得到的并不是格式最好的 json，但我不太想出一种不需要花费我几个小时的方法来做到这一点单个文件。 (我在大约 100 个文件中拥有大约 50 万行 Twitter 数据)。

下面附有我的 json 文件的一 (1) 行示例。

Here's a drive link to one of my smaller files if that helps。

从字面上看，任何方法都可以做到这一点，我们将不胜感激。

谢谢!

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\u092c\u094c\u0928\u094d\u0926\u0935\u093e\u0932","id":3369674594,"id_str":"3369674594","indices":[490,506]},{"screen_name":"LillyMaryPinto","name":"Lilly \u0932\u093f\u0932\u094d\u0932\u0940 \u0cb2\u0cbf\u0cb2\u0ccd\u0cb2\u0cbf \ud83c\uddee\ud83c\uddf3","id":2801729758,"id_str":"2801729758","indices":[507,522]},{"screen_name":"RohiniShah73","name":"Rohini Shah \ud83c\uddee\ud83c\uddf3","id":3300890464,"id_str":"3300890464","indices":[523,536]},{"screen_name":"postcard_news","name":"Post Card","id":3179331468,"id_str":"3179331468","indices":[537,551]},{"screen_name":"MailOnline","name":"Daily Mail Online","id":15438913,"id_str":"15438913","indices":[552,563]},{"screen_name":"EconomicTimes","name":"EconomicTimes","id":39743812,"id_str":"39743812","indices":[564,578]},{"screen_name":"narendramodi","name":"Narendra 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Answer 1

这看起来像 ndjson。 ndjson 和 jsonlite 包都可以处理它。

dat <- ndjson::stream_in("data/INCIndia26febru.json")
# Source: local data table [1,584 x 2,814]
# 
# # A tibble: 1,584 x 2,814
#    contributors coordinates created_at entities.hashta… entities.symbols entities.urls entities.user_m…
#           <int>       <int> <chr>                 <int>            <int>         <int>            <dbl>
#  1           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  2           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  3           NA          NA Tue Feb 2…               NA               NA            NA          2.23e 8
#  4           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
#  5           NA          NA Tue Feb 2…               NA               NA            NA          1.06e18
#  6           NA          NA Tue Feb 2…               NA               NA            NA          1.47e 8
#  7           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
#  8           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
#  9           NA          NA Tue Feb 2…               NA               NA            NA          1.15e 9
# 10           NA          NA Tue Feb 2…               NA               NA            NA          7.44e 7
# # … with 1,574 more rows, and 2,807 more variables: entities.user_mentions.0.id_str <chr>,
# #   entities.user_mentions.0.indices.0 <dbl>, entities.user_mentions.0.indices.1 <dbl>,
# #   entities.user_mentions.0.name <chr>, entities.user_mentions.1.id <dbl>,
# #   entities.user_mentions.0.screen_name <chr>, entities.user_mentions.1.id_str <chr>,
# #   entities.user_mentions.1.indices.0 <dbl>, retweeted_status.entities.user_mentions.0.name <chr>,
# #   retweeted_status.entities.user_mentions.0.screen_name <chr>,
# #   retweeted_status.extended_tweet.display_text_range.0 <dbl>,
# #   retweeted_status.entities.user_mentions.0.id_str <chr>,
# #   retweeted_status.entities.user_mentions.0.indices.0 <dbl>,
# #   retweeted_status.entities.user_mentions.0.indices.1 <dbl>, retweeted_status.entities.urls.0.url <chr>,
# #   retweeted_status.entities.user_mentions.0.id <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.media_url_https <chr>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.h <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.medium.h <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.resize <chr>,
# #   retweeted_status.extended_tweet.entities.media.0.sizes.large.w <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.indices.0 <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.indices.1 <dbl>,
# #   retweeted_status.extended_tweet.entities.media.0.media_url <chr>, in_reply_to_user_id_str <chr>,
# #   in_reply_to_status_id_str <chr>, is_quote_status <lgl>, lang <chr>, id_str <chr>,
# #   in_reply_to_screen_name <chr>, in_reply_to_status_id <dbl>, in_reply_to_user_id <dbl>, retweet_count <dbl>,
# #   place <int>, quote_count <dbl>, retweeted <lgl>, retweeted_status.contributors <int>, reply_count <dbl>,
# #   retweeted_status.coordinates <int>, retweeted_status.created_at <chr>, user.created_at <chr>,
# #   user.contributors_enabled <lgl>, retweeted_status.user.utc_offset <int>,
# #   retweeted_status.user.verified <lgl>, source <chr>, text <chr>, timestamp_ms <chr>, truncated <lgl>,
# #   user.default_profile <lgl>, user.following <int>, user.default_profile_image <lgl>, user.description <chr>,
# #   user.follow_request_sent <int>, user.followers_count <dbl>, user.friends_count <dbl>,
# #   user.favourites_count <dbl>, quoted_status.extended_tweet.extended_entities.media.0.sizes.thumb.resize <chr>,
# #   quoted_status.extended_tweet.extended_entities.media.0.sizes.thumb.w <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.aspect_ratio.0 <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.aspect_ratio.1 <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.type <chr>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.duration_millis <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.video_info.variants.0.bitrate <dbl>,
# #   quoted_status.extended_tweet.extended_entities.media.0.url <chr>,
# #   retweeted_status.entities.hashtags.0.indices.0 <dbl>, retweeted_status.entities.hashtags.0.indices.1 <dbl>,
# #   retweeted_status.entities.hashtags.0.text <chr>, favorite_count <dbl>,
# #   entities.user_mentions.1.indices.1 <dbl>, entities.user_mentions.1.name <chr>,
# #   entities.user_mentions.1.screen_name <chr>, favorited <lgl>, filter_level <chr>, geo <int>, id <dbl>,
# #   retweeted_status.favorite_count <dbl>, retweeted_status.favorited <lgl>, retweeted_status.filter_level <chr>,
# #   retweeted_status.extended_tweet.full_text <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.sizes.thumb.resize <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.sizes.thumb.w <dbl>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.type <chr>,
# #   retweeted_status.extended_tweet.extended_entities.media.1.url <chr>, user.id_str <chr>,
# #   user.is_translator <lgl>, user.lang <chr>, user.listed_count <dbl>, user.location <chr>, user.name <chr>,
# #   user.geo_enabled <lgl>, user.id <dbl>, retweeted_status.display_text_range.0 <dbl>,
# #   retweeted_status.display_text_range.1 <dbl>, retweeted_status.entities.hashtags <int>,
# #   retweeted_status.entities.symbols <int>, retweeted_status.entities.urls.0.display_url <chr>,
# #   retweeted_status.entities.urls.0.expanded_url <chr>, retweeted_status.entities.urls.0.indices.0 <dbl>,
# #   retweeted_status.entities.urls.0.indices.1 <dbl>, retweeted_status.geo <int>, …

或者:

dat <- jsonlite::stream_in(file("data/INCIndia26febru.json"))
tibble::glimpse(dat)
# Observations: 1,584
# Variables: 36
# $ created_at                <chr> "Tue Feb 26 13:09:36 +0000 2019", "Tue Feb 26 13:09:38 +0000 2019", "Tue Feb …
# $ id                        <dbl> 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.100382e+18, 1.10038…
# $ id_str                    <chr> "1100382373823299586", "1100382382396448770", "1100382385013645314", "1100382…
# $ text                      <chr> "RT @INCIndia: Congress President @RahulGandhi addresses North-East DCC &amp;…
# $ source                    <chr> "<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for…
# $ truncated                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ in_reply_to_status_id     <dbl> NA, 1.100360e+18, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_status_id_str <chr> NA, "1100359823630237697", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ in_reply_to_user_id       <dbl> NA, 1.153045e+09, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_user_id_str   <chr> NA, "1153045459", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
# $ in_reply_to_screen_name   <chr> NA, "INCIndia", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ user                      <data.frame> <data.frame[38 x 39]>
# $ geo                       <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ coordinates               <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ place                     <data.frame> <data.frame[38 x 9]>
# $ contributors              <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
# $ retweeted_status          <data.frame> <data.frame[38 x 34]>
# $ is_quote_status           <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, FA…
# $ quote_count               <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ reply_count               <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ retweet_count             <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ favorite_count            <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
# $ entities                  <data.frame> <data.frame[38 x 5]>
# $ favorited                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ retweeted                 <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, …
# $ filter_level              <chr> "low", "low", "low", "low", "low", "low", "low", "low", "low", "low", "low", …
# $ lang                      <chr> "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en", "en",…
# $ timestamp_ms              <chr> "1551186576692", "1551186578736", "1551186579360", "1551186579893", "15511865…
# $ display_text_range        <list> [NULL, <23, 100>, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL…
# $ possibly_sensitive        <lgl> NA, NA, NA, NA, FALSE, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
# $ quoted_status_id          <dbl> NA, NA, NA, NA, NA, NA, 1.100365e+18, NA, NA, 1.100365e+18, NA, NA, 1.100365e…
# $ quoted_status_id_str      <chr> NA, NA, NA, NA, NA, NA, "1100364859768782849", NA, NA, "1100364859768782849",…
# $ quoted_status             <data.frame> <data.frame[38 x 32]>
# $ quoted_status_permalink   <data.frame> <data.frame[38 x 3]>
# $ extended_tweet            <data.frame> <data.frame[38 x 4]>
# $ extended_entities         <data.frame> <data.frame[38 x 1]>