Top Tweets for #GeostatsPy
๐จ New Chapter Alert! ๐จ
A new chapter is now available in my free online e-book:
Applied Geostatistics in Python: A Hands-on Guide with GeostatsPy
In this chapter, I walk through a complete 3D by-facies porosity modeling workflow โ all using #Python and #GeostatsPy (pip install geostatspy)!
๐ ๏ธ Itโs practical, detailed, and built for hands-on learning.
๐ Check it out here:
https://t.co/aCSQa5DwWj
I'm stoked to update and improve my > 40 well-documented #Python #spatial #DataAnalytics workflows with #GeostatsPy. Everything you need, to learn and get the job done!
For example, here's a demonstration of spatial continuity characterization through variogram calculation and modeling on #GitHub @ https://t.co/IYXX6LyiOX โ.
I'm updating and improving my #spatial #DataAnalytics repository on my #GitHub account. Explore more than 40 well-documented demonstrations using the #GeostatsPy #Python package to tackle common modeling tasks!
Including:
Debiasing spatial data
Calculating spatial continuity
Spatial estimation and simulation
Check out this example comparing estimation and simulation, https://t.co/DaY4s4k9Yg โ.
Last week I made major updates to #GeostatsPy, our open-source #Python package for #spatial #DataAnalytics and #geostatistics.
For example, 3D variograms and spatial estimation (appreciation to Prof. @HonggeunJ), along with spatial sampling, declustering, bootstrap, etc. methods.
Learning a new #Python package can be challenging, but well-documented examples make a huge difference!
Iโm excited to announce the release of a new #GitHub repository packed with well-documented workflows that use #GeostatsPy to accomplish common spatial #DataAnalytics and geostatistics tasks.
The repository contains approximately 40 @ProjectJupyter Notebooks, each showcasing a different workflow. Check it out on GitHub @ https://t.co/Zm8NVzu1iM โ. #DataScience #opensource #openeducation
Open-source software with open-education to support students and working professionals!
To support my students, I wrote a #Python package for #spatial #DataAnalytics & #geostatistics, #GeostatsPy, and to help them use it I also built out many well-documented demonstration workflows!
Here's an example for spatial continuity, I take a realistic dataset, Gaussian transform, calculate directional variograms & a variogram map!
I share it on #GitHub at https://t.co/Z9nCBQn05g โ. #DataScience
To support my students I wrote a #spatial #DataAnalytics / #Geostatistic #Python package called #GeostatsPy.
โpip install geostatspyโ to install + many demo workflows to get you started!
I needed reliable, accessible #opensource code for my classes. I wrote many of these functions in the middle of the night just in time for the lectures!
I wrote a #Python #geostatistics package, #GeostatsPy, because there was no #opensource, complete, reliable alternative to support my students in the #Python ecosystem (at the time). I wrote just-in-time for lectures in the mornings!
I also wrote many well-documented demonstration workflows on #github @ https://t.co/vbO1vLTm6f โ. #DataAnalytics Try the GeostatsPy*.ipynb's!
Interested in doing #spatial #DataAnalytics and #geostatistics with #Python? Check out my #opensource Python package, #GeostatsPy.
To help you get started, I built out many demonstration workflows with well-documented Jupyter Notebooks @ https://t.co/bu3A4XoR8b โ. #DataScience
Today could be the day that you try our #spatial #data #debiasing? Powerful spatial #DataScience!
Join me for a walk-through of a well-documented #Python @ProjectJupyter workflow with my #GeostatsPy package & @matplotlib visualization on #Youtube @ https://t.co/v3JJzckYa8 โ.
I'm teaching variogram calculation & modeling today in my #DataAnalytics & #geostatistics course for #spatial prediction! To support my students I wrote a spatial continuity modeller with @matplotlib & #GeostatsPy in #Python. Try it @ https://t.co/iDO7kyeLTs โ. #DataScience
I'm teaching #spatial #estimation & #simulation this week in my #spatial #DataAnalytics course. Both are essential #prediction paradigms for #DataScience. To support my students I made a new #Python #GeostatsPy @matplotlib demo on #github @ https://t.co/tFa9a4r0IB โ.
I made bug fixes for my #Python package #GeostatsPy & update on @pypi. Appreciation to folks that contribute to #opensource by sharing their bug reports. Try it out! I have many demonstration workflow with the package, 'GeostatsPy_*.ipynb' on #github @ https://t.co/V3XwWun2L8 โ.
I gave a #tutorial today at #Transform2021 on #Python #OpenSource #subsurface #DataAnalytics, #geostatistics for #uncertainty #modeling with #GeostatsPy. Appreciation to @swung_org for hosting this fantastic event & for the invitation to participate, @ https://t.co/57LWICOql2 โ.
Today's goal, prepare and post my #TRANSFORM2021 #tutorial on #OpenSource #spatial #DataAnalytics, #geostatistics with the #GeostatsPy #Python package. Appreciation to @swung_org for the invitation to provide a tutorial again this year. Spatial #uncertainty #modeling! I'm stoked!
Did you miss my @swung_org tutorial on #opensource #Spatial #DataAnalytics in #Python with #GeostatsPy? We played with interactive #spatial #statistics! You can still check it out here @ https://t.co/K7ItoA7PYM via @YouTube
I'm excited about the tutorial tomorrow on #subsurface #DataAnalytics with #GeostatsPy package in #Python (on @swung_org's #YouTube channel). Howdy Participants, please join the tutorial #slack channel, and let's make this interactive! Wow, 440 participants last time I checked!
I wrote a short course yesterday 'Open Source #spatial #DataAnalytics in #Python with #GeostatsPy' and posted everything: lectures, datasets & interactive demonstrations on #github @ https://t.co/AwSDBvkxFP. Unsure if you want to attend my tutorial at #TRANSFORM2020? Here it is!
@ThomasM_geo @GoogleColab and I'll be covering @spatial #DataAnalytics / #geostatistics with the new #GeostatsPy #Python package! @ThomasM_geo and I are on a mission to improve code literacy in our #geoscience community.
Reasonable synthetic, exhaustive truth models & sparse sample sets are essential for #spatial #DataAnalytics & #MachineLearning. Here's a #Python workflow with #GeostatsPy & building block functions for making spatial synthetic datasets! On #GitHub @ https://t.co/YaW9seutY6 โ.
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