如何通过从 txt 文件中读取字典列表来创建 Pandas DataFrame？

如何解决如何通过从 txt 文件中读取字典列表来创建 Pandas DataFrame？

我使用 tweepy 下载了 Twitter 数据，并将每条推文存储在 tweet_data 中。

tweet_data = []

for tweet_id in tweet_id_list:
        try:
            tweet_line = api.get_status(tweet_id,trim_user = True,include_my_retweet = False,include_entities = False,include_ext_alt_text = False,tweet_mode = 'extended')
            
            tweet_data.append(tweet_line)

        except:
            continue # if tweet_id not found in twitter,move on to next tweet_id

将 tweet_data 放入 'twitter_json.txt'。

with open('twitter_json.txt','w') as txt:
    for data in tweet_data:
        tweet = data._json
        tweet = json.dumps(tweet)
        try:
            txt.write(tweet + '\n')
        except Exception as e:
            print(e)

这是文本文件中的部分数据。

{"created_at": "Tue Aug 01 16:23:56 +0000 2017","id": sample_01,"id_str": sample_01,"full_text": "This is Phineas. He's a mystical boy. Only ever appears in the hole of a donut. 13/10 ","truncated": false,"display_text_range": [0,85],"extended_entities": {"media": [{"id": 892420639486877696,"id_str": "892420639486877696","indices": [86,109],"media_url": "some_url","media_url_": "some_url","url": some_url,"display_url": some_url,"expanded_url": some_url,"type": "photo","sizes": {"thumb": {"w": 150,"h": 150,"resize": "crop"},"medium": {"w": 540,"h": 528,"resize": "fit"},"small": {"w": 540,"large": {"w": 540,"resize": "fit"}}}]},"source": "<a some_url","in_reply_to_status_id": null,"in_reply_to_status_id_str": null,"in_reply_to_user_id": null,"in_reply_to_user_id_str": null,"in_reply_to_screen_name": null,"user": {"id": 4196983835,"id_str": "4196983835"},"geo": null,"coordinates": null,"place": null,"contributors": null,"is_quote_status": false,"retweet_count": 7427,"favorite_count": 35179,"favorited": false,"retweeted": false,"possibly_sensitive": false,"possibly_sensitive_appealable": false,"lang": "en"}
{"created_at": "Tue Aug 01 00:17:27 +0000 2017","id": sample_02,"id_str": sample_02,"full_text": "This is Tilly. She's just checking pup on you. Hopes you're doing ok. If not,she's available for pats,snugs,boops,the whole bit. 13/10 some_url",138],"extended_entities": {"media": [{"id": 892177413194625024,"id_str": "892177413194625024","indices": [139,162],"url": "some_url","display_url": "some_url","expanded_url": "some_url","medium": {"w": 1055,"h": 1200,"small": {"w": 598,"h": 680,"large": {"w": 1407,"h": 1600,"source": "some_url","retweet_count": 5524,"favorite_count": 30458,"lang": "en"}

下一步...读取 'twitter_json.txt' 文件，我想用 Pandas 创建一个 DataFrame。

with open('twitter_json.txt') as txt:
    data = [line.strip() for line in txt]

这是创建的数据框的快照，结果似乎不太正确。

print(pd.DataFrame(data))

                                                0
0  {"created_at": "Tue Aug 01 16:23:56 +0000 2017...
1  {"created_at": "Tue Aug 01 00:17:27 +0000 2017...

我希望数据框具有诸如“created_at”、“id”、“id_str”等列。我该怎么做？

解决方法

如果您稍微修改您的工作流程，它就会起作用。我使用了不同的写/读例程来完成这项工作。另外，我使用的是我自己的数据，所以输出不会是你的数据。

# create list of json formats first,then write to file    
write_data = [tweet._json for tweet in tweet_data]

# write to file
f = open('twitter_json.txt',"w+")
f.write(json.dumps(write_data))
f.close()

# read with json.loads
with open('twitter_json.txt','rb') as f:
    data = json.loads(f.read().decode('utf-8'))

pd.DataFrame(data)

输出

                       created_at                   id               id_str                                          full_text  truncated display_text_range  ... retweet_count favorite_count favorited retweeted possibly_sensitive lang
0  Fri Jan 08 11:16:09 +0000 2021  1347502345517735940  1347502345517735940  ? La suite du voyage du futur métro d’Hanoï,f...      False           [0,211]  ...             1              3     False     False              False   fr
1  Fri Jan 08 11:15:31 +0000 2021  1347502185920286722  1347502185920286722  ? The continuation of the journey of the futur...      False           [0,211]  ...             1              5     False     False              False   en

[2 rows x 26 columns]