Agronomy4future

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Agronomy4future

Stories about cereals and statistics (plus coding). We aim to develop open-source code for agronomy.

May 30, 2022 JK

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JK Kim 
([email protected]) 
"We aim to develop open-source code for agronomy"

• GitHub: github.com/agronomy4future
• YouTube: @agronomy4future

annotate() aov () arrange() c(rep() case_when() colnames() data.frame() ddply () dplyr facet_grid() facet_wrap() filter() fwrmodel() gdds() geom_abline () geom_bar () geom_vline() github HSD.test() if() ifelse() intercept0() kimindex() mutate() nls() nlsLM() normtools() pivot_longer() poly() predict() probdistz() rbind() reshape2::melt() residuals() sapply() scale_fill_manual () spread() str_replace_all () subset() table() tdist() theme_grey() windows () write_xlsx() xtabs()

New R package: #descriptivestat()
This package automatically embeds descriptive statistics into the dataset, allowing for clear visualization alongside the raw data.

□ Github: https://t.co/tYJPmzvCzJ
□ Code explained: https://t.co/sPOqQwIDgu pic.twitter.com/EL330dIH21
— J.K Kim (@agronomy4future) May 18, 2025

When the intercept is forced to 0 in a simple linear regression, most software programs report an incorrect R². Therefore, I developed a new R package, #intercept0(), which provides the correct R².

□ Github: https://t.co/In3GS6szFI
□ Code explained: https://t.co/EAL3Rbeo6U pic.twitter.com/LJ2eoUlLeT
— J.K Kim (@agronomy4future) May 11, 2025

This is a simple crop growth simulation code based on the Sigmoid Growth Model. If you assume a certain crop growth curve (e.g., biomass or canopy size) over time, you can set up this simulation curve and track it over time. I am sharing the Python code (https://t.co/RiBpXzpXkP) pic.twitter.com/YatW9RcikP
— J.K Kim (@agronomy4future) March 21, 2025

This is a new R package I developed, #datazip(), which enables the simple conversion of data into a single line of code, making it easy to save as a script. Save your data as code for easy access.

□ Github: https://t.co/mNmhyldp98
□ Code explained: https://t.co/8zEgJe0pEF pic.twitter.com/SrkuzVRK7N
— J.K Kim (@agronomy4future) March 7, 2025

I developed an R package, #interpolate() to facilitate data interpolation, particularly by grouping. With this R package, you can easily predict intermediate data points based on actual data points.
□ Github: https://t.co/ClJuZPAMfH
□ Code explained: https://t.co/RRoaphRSi8 pic.twitter.com/u6SVdY1tBO
— J.K Kim (@agronomy4future) March 3, 2025

https://twitter.com/agronomy4future/status/1889715914943119644

https://twitter.com/agronomy4future/status/1878839760493658397

https://twitter.com/agronomy4future/status/1858762408925557136

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https://twitter.com/agronomy4future/status/1689110911028473856

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