KunOnYomiFrequency
cheatsheets
| KunOnYomiFrequency | cheatsheets | |
|---|---|---|
| 1 | 126 | |
| 1 | 7,238 | |
| - | 0.1% | |
| 0.0 | 7.0 | |
| about 3 years ago | 10 days ago | |
| Jupyter Notebook | Python | |
| - | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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KunOnYomiFrequency
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Most Common Possible Readings of the Most Frequently Used Kanji | Python
GitHub: https://github.com/LexingtonWhalen/KunOnYomiFrequency/blob/main/README.md
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
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How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information.
- Matplotlib
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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Getting visual studio code to work with imported library
Name: matplotlib Version: 3.7.1 Summary: Python plotting package Home-page: https://matplotlib.org Author: John D. Hunter, Michael Droettboom Author-email: [email protected] License: PSFLocation: /home/huinker/.local/lib/python3.10/site-packages
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
What are some alternatives?
kanji - Haskell suite for determining what 級 (level) of the 漢字検定 (national Kanji exam) a given Kanji belongs to.
finplot - Performant and effortless finance plotting for Python
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
manim - A community-maintained Python framework for creating mathematical animations.
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.
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Keras - Deep Learning for humans
geogebra - GeoGebra apps (mirror)
OpenCV - Open Source Computer Vision Library
chat-replay-downloader - A simple tool used to retrieve chat messages from livestreams, videos, clips and past broadcasts. No authentication needed!
NumPy - The fundamental package for scientific computing with Python.