[英]How to create Pandas DataFrame by reading list of dictionary from txt file?
我用 tweepy 下載了 Twitter 數據,並將每條推文存儲在 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
將 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)
以下是文本文件中的部分數據。
{"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, "h": 528, "resize": "fit"}, "large": {"w": 540, "h": 528, "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", "truncated": false, "display_text_range": [0, 138], "extended_entities": {"media": [{"id": 892177413194625024, "id_str": "892177413194625024", "indices": [139, 162], "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": 1055, "h": 1200, "resize": "fit"}, "small": {"w": 598, "h": 680, "resize": "fit"}, "large": {"w": 1407, "h": 1600, "resize": "fit"}}}]}, "source": "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": 5524, "favorite_count": 30458, "favorited": false, "retweeted": false, "possibly_sensitive": false, "possibly_sensitive_appealable": false, "lang": "en"}
下一步...閱讀“twitter_json.txt”文件,我想用 pandas 創建一個 DataFrame。
with open('twitter_json.txt') as txt:
data = [line.strip() for line in txt]
這是創建的數據框的快照,結果似乎不太正確。
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 dataframe 有諸如“created_at”、“id”、“id_str”等列。我該怎么做?
如果您稍微修改您的工作流程,它就會起作用。 我使用不同的寫/讀例程來完成這項工作。 另外,我使用的是我自己的數據,所以 output 不會是你的數據。
# 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)
Output
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]
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