View allAll Photos Tagged ggplot2
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
a scatterplot of tweets vs followers for accounts that follow @asianturfgrass. Plot made using ggplot2
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
pink-windows-purple-other-blue-macos-green-linux-2020-10-20-2020-10-20-firefox-desktop-all-locales
colophon:
github.com/rtanglao/rt-r-ggplot2-ruby-experiments/blob/ma...
for h in {0..23} do Rscript ../hourly-ff-question-barcode.R 2020 10 20 $h done
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Quinto semestre
Ciencia de Datos con R es una unidad curricular teórico-práctica que introduce a las y los estudiantes en las herramientas fundamentales para el análisis de datos en R, con un enfoque sistemático y reproducible. A lo largo del curso, se explorarán técnicas de manipulación, visualización y modelado de datos, utilizando los paquetes del tidyverse para garantizar un flujo de trabajo estructurado y eficiente.
Se abordarán modelos básicos de regresión y clasificación, asà como estrategias para la exploración de datos provenientes de encuestas por muestreo, considerando aspectos como la representatividad y los errores de muestreo. Además, se enfatizará la importancia de la investigación reproducible, enseñando a las y los estudiantes a generar reportes dinámicos con Quarto, utilizar Git para control de versiones y desarrollar aplicaciones interactivas con Shiny.
El curso combina clases expositivas con talleres prácticos en laboratorio, promoviendo el aprendizaje activo mediante ejercicios individuales y grupales. Se trabajará en la visualización de datos con ggplot2, asà como en la creación de gráficos interactivos con plotly, permitiendo explorar la información de manera dinámica. Al finalizar el curso, las y los estudiantes que lo cursen van a ser capaces de aplicar métodos estadÃsticos a problemas reales y comunicar sus resultados de manera clara, precisa y efectiva.
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