Code-used-on-Daniel-Lemire-s-blog VS PythonDataScienceHandbook

It's not bad at all https://github.com/lemire/Code-used-on-Daniel-Lemire-s-blog/...

A newline is missing in the example code. As given there's a segfault at line 5 not line 6.

However, the code at https://github.com/lemire/Code-used-on-Daniel-Lemire-s-blog/... shows it's indeed at line 6, because it has an extra newline after the '#include '.

Daniel Lemire's Blog : Daniel Lemire's blog

Dr. Daniel Lemire's blog: https://lemire.me/blog, covers lots of technical items on optimizations in various programming languages, Lemire's work is currently in use across a number of projects and he consistently delivers fantastic improvements, he usually accompanies these improvements with a blog post describing what he did. He also occasionally posts interesting Science and Technology links on various topics not limited to tech, but health and education as well.

Nope, simdjson is originally from Daniel Lemire who also often blogs about fancy low level optimizations: https://lemire.me/blog/ I'm just a happy user :)

Added this pull request with some interesting results.

There's a copy of the loop used on the escape function inside the avx512_escape function [0]. Is it needed or just a copy and paste mistake? (I know nothing about vector instructions)

0: https://github.com/lemire/Code-used-on-Daniel-Lemire-s-blog/...

Python Data Science Handbook

Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data

I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.

Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)

Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.

7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.

I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/