word_cloud VS 1000-most-common-words

wordcloud to make the word clouds

- 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).

Here's a GitHub issue that tracks this.

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.

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!

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.

The project is very heavily based on https://github.com/amueller/word_cloud

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.

I'm looking to learn the 1000 or so most common words in Russian so that i can start understanding more by context. I want a list where I can make the words into flashcards on Anki. Already tried 1000mostcommonwords.com but some of the words seem wrong.

The 1000 most common words are probably going to be the most important. You can find them here for many languages. Most people will come across these top 1000 in their beginner learning season since many of these words are things like “he, she, it, I, am, want, there, etc,” the sheer basic building blocks of language

My impression of 1000mostcommonwords.com is that they got a nice domain name and got search hits, and put up a minimal word list for many commonly searched-for languages. The word list is probably not that bad, but it's not spectactular either, and they don't give any details on how they constructed it or what their methodology is at all.

I've found this website, which contains lists of 1000 words for a lot of different languages, and I thought about using it for namebases. To make things faster I wrote this little JavaScript snippet to retrieve a comma-separated list of words from the table. To get a namebase, just open the page for the language of your choice, run the code, and copy-paste the generated namebase into FMG.