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followers: 34.0 following: 29.0 repos: 60.0 gists: 3.0

Name: Julia Piaskowski

Type: User

Company: University of Idaho

Bio: data jockey and ag statistician @ University of Idaho

Twitter: seedsandbreeds

Location: Moscow, ID

Blog: https://jpiaskowski.gitlab.io/

Hello

I'm Julia Piaskowski, a statistician at the University of Idaho, College of Agriculture and Life Sciences. I try to provide resources to support high quality analysis of agriculture studies and adjacent research. I view myself as a 'user advocate' attempting to bridge the gap between complex statistical methodologies/tools and what users actually need to use those. I'm also a Software Carpentries certified instructor.

Some Resources I maintain or help maintain 🔧

Agriculture CRAN Task View: to find that R package supporting your agriculture research needs.
[Mixed Model CRAN Task View)(https://CRAN.R-project.org/view=MixedModels): to find that mixed modellling package in R
Introductory R for Scientists: zero-to-hero coursework content for learning R!
University of Idaho Agricultural Statistics Resources Website: collection of tutorials, workshops and blog posts supporting analysis of research data
[Field Guide to Incorporating Spatial Covariates into Analysis of Planned Field Experiments](Agricultural Field Experiments
Irregular Newsletter on Ag Stats: sent a few times per year
WAVE: Western Agriculture Variety Explorer: for accessing variety testing data from Idaho, Oregon and Washington

Other Stuff 💬

I'm currently working on building guides to linear mixed modelling, generalized linear mixed modelling and reproducible research for busy scientists (links forthcoming when the resources are complete).

My personal website is actually deployed through GitLab, but I use GitHub for most things. I'm currently working on a new theme for my website (hello, scss!), so the current website is not being maintained since a changeover is planned. I also blog on prison and criminal justice issues here.

Julia Piaskowski's Projects

mixedmodels-misc

miscellaneous materials for mixed models, mostly in R

mixedmodels-taskview

draft R task view for mixed models

mm_workshops

master repo for mixed model workshop material

my_website_hugo

nccc170-website

A website for NCCC-170

new-computer

An extremely opinionated and highly personalized script to set up a new Mac machine, just the way I like it!

openmendel.github.io

The main website for the OpenMendel project.

pycas2020_web_scraping

Short presentation on web scraping using beautiful soup for the Pycascades conference held February, 2020.

r-novice-agscience

SWC-adapted R training for ag scientists

r-novice-gapminder

Introduction to R for non-programmers using gapminder data.

rtimes

R wrapper for NYTimes API for government data - ABANDONED

shinymobile

shiny API for Framework7 (IOS/android)

soilhealthdb

spatial

CRAN Task View: Analysis of Spatial Data

sta210-s22-template

svyvgam

Design-based inference for VGAM

synbreed

Originally forked from the read-only mirror of the CRAN R package repository. synbreed — Framework for the Analysis of Genomic Prediction Data using R. Homepage: http://synbreed.r-forge.r-project.org/

synbreeddata

:exclamation: This is a read-only mirror of the CRAN R package repository. synbreedData — Data for the Synbreed Package. Homepage: http://synbreed.r-forge.r-project.org/

synthwave85

A 80s style theme for RStudio v1.2+

thinkjulia.jl

Port of the book Think Python to the Julia programming language

tidy_tues

Data visualizations for Tidy Tuesday exercises

tidybiology-lectures

A series of 5 lectures introducing Data Science for biological scientists with little to no experience in R

tidyexplain

Animations of tidyverse verbs using R, the tidyverse, and gganimate

tidytuesday

📊 My contributions to the #TidyTuesday challenge

tweet-conf-dash

A shiny twitter conference dashboard

userfaster

for a tutorial at useR2018

wikipedia-biography-dataset

This dataset gathers 728,321 biographies from wikipedia. It aims at evaluating text generation algorithms. For each article, we provide the first paragraph and the infobox (both tokenized).

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