word_cloud
Jieba
| word_cloud | Jieba | |
|---|---|---|
| 28 | 6 | |
| 9,946 | 32,422 | |
| - | - | |
| 6.8 | 0.0 | |
| 4 months ago | about 2 months ago | |
| Python | Python | |
| MIT License | MIT License |
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word_cloud
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[OC] How Many Chinese Characters You Need to Learn to Read Chinese!
wordcloud to make the word clouds
- [OC] 🎶 Lost in a world of music 🎶😉 #MusicLover #GuessTheArtist 🎧🎵🎶
- Unable to install pip install word cloud
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Made a banner with codes and AI [details in comments]
- Logo with WordCloud. The texts used were from the plot/synopsis from the Wikipedia pages of the top 20 anime according to MyAnimeList (excluding anime from the same series. I'm looking at you Gintama).
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Cant get pip to install wordcloud on Mac OS VENTURA python 3.11
Here's a GitHub issue that tracks this.
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[OC] The most common terms in Wikipedia's "Current Events" between January 2003 and September 2022
Word arrangement generated using the wordcloud Python package with a custom placement mask (skull design by me) and custom color function. Common English words removed before processing.
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Generate Word Cloud using Python
After reading this tutorial you should now be able to generate your own Wordcloud using Python. Checkout the WordCloud for Python Documentation. Use your imagination and have fun. Please leave like or comment if you found this article interesting!
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The Sword Of Feedback - Part II
If you are proficient with Python then there is also the wordcloud library (and its homepage/documentation) to make a custom word cloud for yourself rather than relying on TagCrowd. For example, I noticed that using the HasteBin as a URL source caused TagCrowd to put some gibberish words in the cloud, like “donaeurtmt”, which do not appear when simply pasting the raw text into the text field.
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Feedback Request: Word Cloud Generator
The project is very heavily based on https://github.com/amueller/word_cloud
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Best way to find patterns/keywords etc through mass amount of email?
A quick and easy way to get some context into anything being mentioned ensure the CSV is only the responses and run it through a word cloud generator in Python to determine what those keywords are. That should help you see what your customers are at least mentioning and then go from there to look for surrounding context.
Jieba
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[OC] How Many Chinese Characters You Need to Learn to Read Chinese!
jieba to do Chinese word segmentation
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Sentence parser for Mandarin?
Jieba: Chinese text segmenter
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How many in here use google sheets to keep track on their Chinese vocabulary? (2 pics) - More info in the comments
If you know some python you can use a popular library called Jieba 结巴 to automatically get pinyin for every word. (Jieba has actually been ported to many languages) You can also use it to break a chinese text into a set of unique words for easy addition to your spreadsheet.
- Where can I download a database of Chinese word classifications (noun, verb, etc)
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Learn vocabulary effortlessly while browsing the web [FR,EN,DE,PT,ES]
Since you're saying the main issue is segmentation, there are libraries to help out with that issue. jieba is fantastic if you have a Python backend, nodejieba (50k downloads/week) if it's more JS-side.
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I'm looking for a specific vocab list
https://github.com/fxsjy/jieba/ (has some good word frequency data)
What are some alternatives?
scattertext - Beautiful visualizations of how language differs among document types.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
chat-replay-downloader - A simple tool used to retrieve chat messages from livestreams, videos, clips and past broadcasts. No authentication needed!
SnowNLP - Python library for processing Chinese text
chat-miner - Parsers and visualizations for chats
NLTK - NLTK Source
stretchly - The break time reminder app
pkuseg-python - pkuseg多领域中文分词工具; The pkuseg toolkit for multi-domain Chinese word segmentation
reddit_api - A python wrapper for the Reddit API. I originally created this repo, and have since transferred ownership to the praw-dev (PRAW: Python Reddit API Wrapper) organization to allow this project to continue to grow. This fork is here to preserve old links, please head to the praw-dev/praw repo for the latest code.
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
pastevents - A structured, searchable archive of Wikipedia's "Current Events" portal
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.