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https://github.com/mpru/ggcleveland
Implementation of plots from Cleveland's Visualizing Data book in ggplot2
https://github.com/mpru/ggcleveland
Last synced: 3 days ago
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Implementation of plots from Cleveland's Visualizing Data book in ggplot2
- Host: GitHub
- URL: https://github.com/mpru/ggcleveland
- Owner: mpru
- Created: 2020-05-12T02:42:49.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-09-29T16:15:00.000Z (about 3 years ago)
- Last Synced: 2024-09-20T00:41:59.179Z (about 2 months ago)
- Language: R
- Size: 7.6 MB
- Stars: 8
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
---
output: github_document
editor_options:
chunk_output_type: console
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>", error = FALSE, message = FALSE,
fig.path = "man/figures/README-",
# out.width = "70%",
fig.align = "center"
)
```
# ggcleveland 
## Gráficos para Análisis Exploratorio de Datos
## Plots for Exploratory Data Analysis
[](https://lifecycle.r-lib.org/articles/stages.html)
[](https://CRAN.R-project.org/package=ggcleveland)
[](https://CRAN.R-project.org/package=ggcleveland)
---
Web: [https://mpru.github.io/ggcleveland/](https://mpru.github.io/ggcleveland/)
CRAN:
---
El libro *Visualizing Data* de William S. Cleveland es una pieza clásica en la literatura sobre Análisis Exploratorio de Datos (AED). Habiendo sido escrito algunas décadas atrás, su contenido sigue siendo relevante ya que propone herramientas útiles para descubrir patrones y relaciones en los datos estudiados, como así también para evaluar ajustes. Este paquete ofrece funciones que producen la versión en `ggplot2` de las herramientas de visualización descriptas en este libro. Fue diseñado como material complementario en cursos sobre AED.
---
William S. Cleveland's book 'Visualizing Data' is a classic piece
of literature on Exploratory Data Analysis (EDA). Although it was written
several decades ago, its content is still relevant as it proposes several
tools which are useful to discover patterns and relationships among the data
under study, and also to assess the goodness of fit o a model. This package
provides functions to produce the ggplot2 versions of the visualization tools
described in this book and is thought to be used in the context of courses on
EDA.
## Instalación / Instalation
Podés instalar `ggcleveland` desde [CRAN](https://CRAN.R-project.org/package=ggcleveland) / You can install `ggcleveland` from [CRAN](https://CRAN.R-project.org/package=ggcleveland):
``` r
install.packages("ggcleveland")
```
También podés instalar la versión en desarrollo del paquete `ggcleveland` desde [GitHub](https://github.com/mpru/ggcleveland) / You can also install the development version from [GitHub](https://github.com/mpru/ggcleveland):
``` r
# install.packages("devtools")
devtools::install_github("mpru/ggcleveland")
```
## Ejemplos / Examples
Podés ver ejemplos de cada una de los gráficos producidos con este paquete en las viñetas. Algunos de ellos son:
---
You can explore examples of each of the plots produced by this package in the vignettes. Some of them are:
*Gráficos condicionales / Coplots*:
```{r, fig.width=6, fig.height=5}
library(ggcleveland)
library(dplyr)
library(ggplot2)
theme_set(theme_bw() + theme(panel.spacing = unit(0, "lines")))
data(rubber)
gg_coplot(rubber, x = tensile.strength, y = abrasion.loss, faceting = hardness,
number_bins = 6, overlap = 3/4,
ylabel = "Pérdida de abrasión (g/hp-hour))",
xlabel = "Resistencia a la tracción (kg/cm2)",
facet_label = "Dureza (grados Shore)",
loess_family = "symmetric", size = 2)
```
*Residual-Fit plots*:
```{r, fig.height=2.5, fig.width=6}
data(futbol)
futbol <-
futbol %>%
group_by(longp) %>%
mutate(ajuste = mean(dist), res = dist - ajuste)
gg_rf(futbol, dist, ajuste, res, cen_obs = TRUE, ylabel = "Distancia (m)")
```
*Gráfico Media-Diferencia de Tukey / Tukey's MD Plot*:
```{r, fig.width=6, fig.height=6}
gg_tmd(futbol, dist, longp, size = 0.5)
```