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Nutrient
Nutrient - The #1 PDF SDK Library. Bad PDFs = bad UX. Slow load times, broken annotations, clunky UX frustrates users. Nutrient’s PDF SDKs gives seamless document experiences, fast rendering, annotations, real-time collaboration, 100+ features. Used by 10K+ devs, serving ~half a billion users worldwide. Explore the SDK for free.
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chat-replay-downloader
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reddit_api
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1000-most-common-words
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SaaSHub
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word_cloud discussion
word_cloud reviews and mentions
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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.
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A note from our sponsor - Nutrient
nutrient.io | 16 Feb 2025
Stats
amueller/word_cloud is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of word_cloud is Python.