|about 2 months ago||3 months ago|
|Mozilla Public License 2.0||Apache License 2.0|
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.
Will Rust-based data frame library Polars dethrone Pandas? We evaluate on 1M+ Stack Overflow questions
9 projects | reddit.com/r/rust | 25 May 2022
We didn't conduct our own benchmarks for this post, but in this comparison from ~1 year ago, Polars emerged as the fastest https://h2oai.github.io/db-benchmark/
Amazon Redshift Re-Invented
1 project | news.ycombinator.com | 24 May 2022
DuckDB's is in constant development but doesn't yet have native cross-version export/import feature (since its developers claim DuckDB hasn't reached maturity to stabilise its on-disk formats just yet).
I also keep an eye on https://h2oai.github.io/db-benchmark/ Pola.rs and DataFusion sound the most exciting.
It also remains to be seen how DataBrick's delta.io develops (might come in handy for much much larger datasets).
C++ for data analysis
2 projects | reddit.com/r/cpp | 18 May 2022
Fast Lane to Learning R
4 projects | news.ycombinator.com | 14 May 2022
I strongly recommend data.table R. Tidyverse is an improvement on base R, no question. Data.table has less intuitive syntax and can be harder to learn, but is lightning fast and memory efficient. If you're working with more than 1M rows, you should be using data.table.
Here are some benchmarks: https://h2oai.github.io/db-benchmark/
Friendlier SQL with DuckDB
8 projects | news.ycombinator.com | 12 May 2022
Hi, good to hear that you guys care about testing. One thing apart from the Github issues that led me to believe it might not be super stable yet was the benchmark results on https://h2oai.github.io/db-benchmark/ which make it look like it couldn't handle the 50GB case due to a out of memory error. I see that the benchmark and the used versions are about a year old so maybe things changed a lot since then. Can you chime in regarding the current story of running bigger DBs like 1TB on a machine with just 32GB or so RAM? Especially regardung data mutations and DDL queries. Thanks!
I used a new dataframe library (polars) to wrangle 300M prices and discover some of the most expensive hospitals in America. Code/notebook in article
2 projects | reddit.com/r/Python | 9 May 2022
Per these benchmarks it appears Polars is an order of magnitude more performant and it's lazy and Rust is just kinda sexy.
Benchmarking for loops vs apply and others
2 projects | reddit.com/r/rstats | 1 May 2022
This is a much more comprehensive set of benchmarks: https://h2oai.github.io/db-benchmark/
Why is R viewed badly over here? Also, as a college student, should I prioritize Python instead?
1 project | reddit.com/r/datascience | 29 Apr 2022
Its not like pandas is faster than tidyverse either on all the bechmarks, and data.table is faster than both. https://h2oai.github.io/db-benchmark/
Resources for data cleaning
2 projects | reddit.com/r/rstats | 13 Apr 2022
Language isn't really important here; what's important is tooling, and R definitely has the tooling. I would look at this benchmark reference for database-like operations, and you'll see that data.table (a very fast and memory-efficient R package) consistently ranks as one of the fastest tools out there that can also support a wide range of memory loads.
The fastest tool for querying large JSON files is written in Python (benchmark)
16 projects | news.ycombinator.com | 12 Apr 2022
Turning database into a searchable dashboard?
3 projects | reddit.com/r/datascience | 21 Oct 2021
Oh what's that you say, your data is in CSV and you don't want to write code to load them up into a database, well try this https://github.com/simonw/csvs-to-sqlite
Show HN: Work with CSV files using SQL. For data scientists and engineers
10 projects | news.ycombinator.com | 18 Jul 2021
The datasette author offers this tool for conversion: https://github.com/simonw/csvs-to-sqlite
Datasette 0.58: The annotated release notes
1 project | reddit.com/r/Python | 16 Jul 2021
There's csvs-to-sqlite which allows converting CSVs to SQLite (dumping part of another database to CSV should be more or less trivial). There's also Dogsheep, which can convert more esoteric data sources like GitHub and HackerNews to SQLite. Recently, Simon worked on Django SQL Dashboard, which brings a subset of Datasette to Django.
I made a regexp cheatsheet for grep, sed, awk and highlighted differences between them
5 projects | reddit.com/r/commandline | 1 Jun 2021
And sometimes it's nice to throw csv files into a database. You can do that with https://github.com/simonw/csvs-to-sqlite
What are some alternatives?
arrow-datafusion - Apache Arrow DataFusion SQL Query Engine
polars - Fast multi-threaded DataFrame library in Rust | Python | Node.js
databend - A modern Elasticity and Performance cloud data warehouse, activate your object storage for real-time analytics.
sktime - A unified framework for machine learning with time series
disk.frame - Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data
DataFramesMeta.jl - Metaprogramming tools for DataFrames
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
arrow2 - Unofficial transmute-free Rust library to work with the Arrow format
julia - The Julia Programming Language
DataFrame - C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
sqlitebrowser - Official home of the DB Browser for SQLite (DB4S) project. Previously known as "SQLite Database Browser" and "Database Browser for SQLite". Website at: