I recently concluded 2 urban #datascience projects that I dreamt of doing since a long time, with 2 super talented MSc students who visited us @nerdsitu last year from Germany, Carlson @cbueth and Henrik @supergrobi.
I think in PowerShell and can manage in Python. I want to learn Rust to the degree I can write in it directly, rather than prototyping in PowerShell and then converting.
A lot of what I do is data manipulation and analysis. (Take several CSV files as input, and output new CSV files that answer business questions based on the inputs.) I'm seriously impressed with Rust's performance here.
If you've made this transition, advice on where to begin?
Version 1.7.1 of the NeuralForecast #Python library was released last month by Nixtla. The NeuralForecast library, as the name implies, provides a neural network framework for time series forecasting. 🧵👇🏼
I'll be hosting Michigan Python tomorrow at 7pm EDT. Justin Smethers will be giving a talk about how DuckDB can be used to speed up your data analysis in Python. All are welcome online or in person. #Python#DataSciencehttps://meetu.ps/e/N1csW/t4QC5/i
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Request for testing/comment: can any #rstats users out there give the #wip {styler.equals} package a spin and kick its metaphorical tires 🚲 ? Install with remotes::install_github("robinlovelace/styler.equals") and see more at https://github.com/Robinlovelace/styler.equals Especially for those who prefer typing = over <- due to laziness or any other reason! Not intending to start a flame war 🔥 arrows are great too ⬅️ Any comments/suggestions welcome 🙏 #rspatial#DataScience#style
The course is beginner-level, and it covers topics such as:
✅ Setting an account and managing the cost
✅ Set EC2 instance
✅ Work with S3 objects
✅ Create AWS Lambda function
✅ Create and deploy applications
The talks from the Data Council Austin '24 conference are now available to watch. The Data Council Austin conference focuses on data science and engineering topics. Among the 86 talks, you can find talks about topics such as time series analysis, working with different databases, ETL, machine learning, GenAI, etc.
Request for help from anyone with #rstats package development experience or knowledge of time data, especially if you've worked with .ical files before: checks failing in the {calendar} package preventing updated on CRAN and I'm not sure why 🤷 . Thanks to new contributors for reviving this package after ~5 years dev hiatus! Please spread the word @rOpenSci and anyone in this #foss for #DataScience (or at least dates) space! Details: https://github.com/ATFutures/calendar/issues/50
(1/3) I am excited to share that my course - Data Pipeline Automation with GitHub Actions Using R and Python 🚀, is now available on LinkedIn Learning!
The course provides an introduction to setting up automation with GitHub Actions with both R and Python. Throughout the course, we will use a real-life example by working with the U.S. Energy Information Administration (EIA) API for data automation. 🧵👇🏼
Excited to announce the release of {stplanr} v1.2.0, on CRAN and beyond 🎉
Key feature: new implementation of rnet_join(), allowing fast+flexible merging of route network datasets, leveraging {rsgeo} which has a fast (~1000x faster than {lwgeom}) #RustLang backend 🔥
Many people to thank for this release 🙏
It's been almost 8 years since {stplanr} v0.01 was released to support #DataScience tools for #Transportation planning. The first major use case was the Propensity to Cycle Tool 🚲 now publicly available at https://pct.bike
📣 Exciting news, everyone! 🌟 Make sure to head over to this weeks blog "What's new in R 4.4.0?" by Russ Hyde, and dive into the world of the latest R release📊🔬💻
Discover some of the amazing new features that this version has to offer! 🔍 🔭 🚀