KunOnYomiFrequency
The most common possible readings of the most frequently used Kanji characters. (by lxaw)
kanji
Haskell suite for determining what 級 (level) of the 漢字検定 (national Kanji exam) a given Kanji belongs to. (by fosskers)
| KunOnYomiFrequency | kanji | |
|---|---|---|
| 1 | - | |
| 1 | 22 | |
| - | - | |
| 0.0 | 0.0 | |
| about 3 years ago | over 2 years ago | |
| Jupyter Notebook | Haskell | |
| - | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
KunOnYomiFrequency
Posts with mentions or reviews of KunOnYomiFrequency.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-03.
-
Most Common Possible Readings of the Most Frequently Used Kanji | Python
GitHub: https://github.com/LexingtonWhalen/KunOnYomiFrequency/blob/main/README.md
kanji
Posts with mentions or reviews of kanji.
We have used some of these posts to build our list of alternatives
and similar projects.
We haven't tracked posts mentioning kanji yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
When comparing KunOnYomiFrequency and kanji you can also consider the following projects:
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
compendium-client - Mu (μ) is a purely functional framework for building micro services.
NBA-attendance-prediction - Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.
bookkeeping-jp - Helper functions of Haskell bookkeeping module for Japanese bookkeeping.