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Take A QuizGeneral Tech Bugs & Fixes 2 years ago
Posted on 16 Aug 2022, this text provides information on Bugs & Fixes related to General Tech. Please note that while accuracy is prioritized, the data presented might not be entirely correct or up-to-date. This information is offered for general knowledge and informational purposes only, and should not be considered as a substitute for professional advice.
First decode
values to utf-8
and convert to dictionaries in list comprehension by ast.literal_eval
or json.loads
:
data = [b'{"word": "Gondwana", "date": "20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">12.404732"}',
b'{"word": "alalus", "date": "20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">12.9095b.com/tag/1">17"}',
b'{"word": "Balto-Slavonic", "date": "20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">14.9b.com/tag/1">1b.com/tag/1">1308"}',
b'{"word": "peculatation", "date": "20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">15.42b.com/tag/1">19b.com/tag/1">15"}']
b.com/tag/import">import ast
df = pd.DataFrame([ast.literal_eval(x.decode("utf-8")) for x in data])
print (df)
date word
0 20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">12.404732 Gondwana
b.com/tag/1">1 20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">12.9095b.com/tag/1">17 alalus
2 20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">14.9b.com/tag/1">1b.com/tag/1">1308 Balto-Slavonic
3 20b.com/tag/1">19-03-27 b.com/tag/1">13:07:b.com/tag/1">15.42b.com/tag/1">19b.com/tag/1">15 peculatation
Alternative solution, should be faster in large data:
b.com/tag/import">import json
df = pd.DataFrame([json.loads(x.decode("utf-8")) for x in data])
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manpreet Best Answer 2 years ago
What is the best possible way to convert my data to DataFrame?
I tried this. Didn't seem to work.