Learn How to Create Animated Graphs in Python
The basics of animated data visualisation
https://towardsdatascience.com/learn-how-to-create-animated-graphs-in-python-fce780421afe
The basics of animated data visualisation
https://towardsdatascience.com/learn-how-to-create-animated-graphs-in-python-fce780421afe
What programming language has the happiest developers?
https://medium.com/swlh/what-programming-language-has-the-happiest-developers-f0636b08e898
https://medium.com/swlh/what-programming-language-has-the-happiest-developers-f0636b08e898
41 Questions to Test your Knowledge of Python Strings
How to crush algorithm questions by mastering…
https://towardsdatascience.com/41-questions-to-test-your-knowledge-of-python-strings-9eb473aa8fe8
How to crush algorithm questions by mastering…
https://towardsdatascience.com/41-questions-to-test-your-knowledge-of-python-strings-9eb473aa8fe8
7 Commands in Python to Make Your Life Easier
Useful commands for IPython and Jupyter Notebooks
https://medium.com/better-programming/7-commands-in-python-to-make-your-life-easier-d48dd0992b57
Useful commands for IPython and Jupyter Notebooks
https://medium.com/better-programming/7-commands-in-python-to-make-your-life-easier-d48dd0992b57
home-assistant / core
🏡 Open source home automation that puts local control and privacy first
https://github.com/home-assistant/core
🏡 Open source home automation that puts local control and privacy first
https://github.com/home-assistant/core
GitHub
GitHub - home-assistant/core: :house_with_garden: Open source home automation that puts local control and privacy first.
:house_with_garden: Open source home automation that puts local control and privacy first. - home-assistant/core
facebookresearch / ParlAI
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
https://github.com/facebookresearch/ParlAI
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
https://github.com/facebookresearch/ParlAI
GitHub
GitHub - facebookresearch/ParlAI: A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
A framework for training and evaluating AI models on a variety of openly available dialogue datasets. - facebookresearch/ParlAI
How to Think of Pandas Data Visualization If You’re Coming From Excel
Building a Mental Model for Data…
https://towardsdatascience.com/how-to-think-of-pandas-data-visualization-if-youre-coming-from-excel-7af9f933e212
Building a Mental Model for Data…
https://towardsdatascience.com/how-to-think-of-pandas-data-visualization-if-youre-coming-from-excel-7af9f933e212
Manisso / fsociety
fsociety Hacking Tools Pack – A Penetration Testing Framework
https://github.com/Manisso/fsociety
fsociety Hacking Tools Pack – A Penetration Testing Framework
https://github.com/Manisso/fsociety
GitHub
GitHub - Manisso/fsociety: fsociety Hacking Tools Pack – A Penetration Testing Framework
fsociety Hacking Tools Pack – A Penetration Testing Framework - Manisso/fsociety
derv82 / wifite2
Rewrite of the popular wireless network auditor, "wifite"
https://github.com/derv82/wifite2
Rewrite of the popular wireless network auditor, "wifite"
https://github.com/derv82/wifite2
GitHub
GitHub - derv82/wifite2: Rewrite of the popular wireless network auditor, "wifite"
Rewrite of the popular wireless network auditor, "wifite" - derv82/wifite2
Python Developers Survey 2019 Results
In the fall of 2019, the Python Software Foundation and JetBrains together conducted the official third annual Python Developers Survey.
https://www.jetbrains.com/lp/python-developers-survey-2019/
In the fall of 2019, the Python Software Foundation and JetBrains together conducted the official third annual Python Developers Survey.
https://www.jetbrains.com/lp/python-developers-survey-2019/
JetBrains: Developer Tools for Professionals and Teams
Python Developers Survey 2019 Results
Official Python Developers Survey 2019 by Python Software Foundation and JetBrains: more than 24k responses from more than 150 countries.
oreilly-japan / deep-learning-from-scratch
『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)
https://github.com/oreilly-japan/deep-learning-from-scratch
『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)
https://github.com/oreilly-japan/deep-learning-from-scratch
GitHub
GitHub - oreilly-japan/deep-learning-from-scratch: 『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)
『ゼロから作る Deep Learning』(O'Reilly Japan, 2016). Contribute to oreilly-japan/deep-learning-from-scratch development by creating an account on GitHub.
8 VS Code Extensions You Might Love
CodeSnap, GitHub Markdown Preview, Paste JSON as Code, and more
https://medium.com/better-programming/8-vs-code-extensions-you-might-love-eba03d85fd4f
CodeSnap, GitHub Markdown Preview, Paste JSON as Code, and more
https://medium.com/better-programming/8-vs-code-extensions-you-might-love-eba03d85fd4f
Resources I Wish I Knew When I Started Out With Data Science
A Powerful Learning Guide for Serious…
https://towardsdatascience.com/resources-i-wish-i-knew-when-i-started-out-with-data-science-9a8889654c36
A Powerful Learning Guide for Serious…
https://towardsdatascience.com/resources-i-wish-i-knew-when-i-started-out-with-data-science-9a8889654c36
Top 5 Mistakes You Make When Declaring Functions in Python
Write better functions
https://medium.com/better-programming/top-5-mistakes-you-make-when-declaring-functions-in-python-b7a0747711a4
Write better functions
https://medium.com/better-programming/top-5-mistakes-you-make-when-declaring-functions-in-python-b7a0747711a4
How to use Jupyter Notebooks in 2020 (Part 3: Final thoughts)
This is the last of a three-part blog post on the Jupyter Notebook ecosystem.
Here, I’ll share ...
https://ljvmiranda921.github.io/notebook/2020/03/30/jupyter-notebooks-in-2020-part-3/
This is the last of a three-part blog post on the Jupyter Notebook ecosystem.
Here, I’ll share ...
https://ljvmiranda921.github.io/notebook/2020/03/30/jupyter-notebooks-in-2020-part-3/
Lj Miranda
How to use Jupyter Notebooks in 2020 (Part 3: Final thoughts)
In the final part of this series, I'd like to share my reflections and wishlist on the Jupyter Notebook ecosystem. Before I end, I'd like to thank you all fo...
Atom’s Hydrogen for writing data science projects with Python
https://towardsdatascience.com/atoms-hydrogen-for-writing-data-science-projects-using-python-46b6507fcdf7
https://towardsdatascience.com/atoms-hydrogen-for-writing-data-science-projects-using-python-46b6507fcdf7
pcomputo / Whole-Foods-Delivery-Slot
Automated script for Whole Foods and Amazon Fresh delivery slot
https://github.com/pcomputo/Whole-Foods-Delivery-Slot
Automated script for Whole Foods and Amazon Fresh delivery slot
https://github.com/pcomputo/Whole-Foods-Delivery-Slot
GitHub
GitHub - pcomputo/Whole-Foods-Delivery-Slot: Automated script for Whole Foods and Amazon Fresh delivery slot
Automated script for Whole Foods and Amazon Fresh delivery slot - GitHub - pcomputo/Whole-Foods-Delivery-Slot: Automated script for Whole Foods and Amazon Fresh delivery slot
How to Progress Rapidly as a Developer
Every craft has a set of foundational skills. Here’s what’s…
https://medium.com/better-programming/how-to-progress-rapidly-as-a-developer-39a282ead61e
Every craft has a set of foundational skills. Here’s what’s…
https://medium.com/better-programming/how-to-progress-rapidly-as-a-developer-39a282ead61e
Introduction to Pandas Equivalents of various SQL queries
An intuitive tutorial for beginners and…
https://towardsdatascience.com/introduction-to-pandas-equivalents-of-various-sql-queries-448fb57dd9b9
An intuitive tutorial for beginners and…
https://towardsdatascience.com/introduction-to-pandas-equivalents-of-various-sql-queries-448fb57dd9b9
Game type: Runner. Time to build: 2 days. Lines of code: 310. Game quality: 100,000,000. That's all the information you need.
https://www.reddit.com/r/Python/comments/geb708/game_type_runner_time_to_build_2_days_lines_of/
https://www.reddit.com/r/Python/comments/geb708/game_type_runner_time_to_build_2_days_lines_of/
reddit
Game type: Runner. Time to build: 2 days. Lines of code: 310. Game...
Posted in r/Python by u/savoiry1 • 9 points and 2 comments