Clase 25 de Sept
Debora Elías Díaz
2023-09-25
LO DE ARRIBA SE CONOCE COMO YALM
Ejercicio 1 Clase
Importar base de datos con dirección relativa:
Base de datos: Denominada Iris.
ir <- read.csv("./data/raw/iris2.csv")
head(ir)## X Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 1 5.1 3.5 1.4 0.2 setosa
## 2 2 4.9 3.0 1.4 0.2 setosa
## 3 3 4.7 3.2 1.3 0.2 setosa
## 4 4 4.6 3.1 1.5 0.2 setosa
## 5 5 5.0 3.6 1.4 0.2 setosa
## 6 6 5.4 3.9 1.7 0.4 setosalargoFlor <- ir[ir$Sepal.Length == "largo", ]
write.csv(x = largoFlor, file = "./data/raw/largoFlor.csv")LargoFlor <- read.csv(file = "./data/raw/LargoFlor.csv")Figuras
Figura 1: Flores Iris
library(knitr)include_graphics("./Images/Fg3.png")
Figura 2: Flores Iris 2
Floreado # para resaltar el texto
include_graphics("./Images/op.gif")
Figura 3: Tipo Gif
Enlaces
figshare
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a## [1] "uno"#Gráficos
Utilizando argumento “eval = TRUE”
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Utilizando argumento “eval = FALSE”
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")Utilizando argumento “collapse = TRUE”
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Utilizando argumento “collapse = FALSE”
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Utilizando argumento “out.width =”80”
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Reduce o amplia tamaño de las imagenes
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
El tamaño de las imagenes está dado por los valores de fig.
Utilizando argumento fig.width: Nota: Se modificaron los tamaños de los textos de los ejes y títulos. Cómo se muestra la imagen en ancho y largo.
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Utilizando argumento fig.height
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Utilizando argumento dpi
boxplot(ir$Sepal.Length ~ ir$Species, col = "#3CB371", ylab = "Sepal length", xlab = "Species")
Incrustación de código en el texto. Dos formas:
1. muestra el código sin ser evaluado.
2. muestra el código y es evaluado (se imprime el resultado de la
evaluación). r.mean(iris$Sepal.Length)`
mean(ir$Sepal.Length)
NA
ir$Sepal.Length## [1] 5.1 4.9 4.7 4.6 5.0 5.4 4.6 5.0 4.4 4.9 5.4 4.8 4.8 4.3 5.8 5.7 5.4 5.1
## [19] 5.7 5.1 5.4 5.1 4.6 5.1 4.8 5.0 5.0 5.2 5.2 4.7 4.8 5.4 5.2 5.5 4.9 5.0
## [37] 5.5 4.9 4.4 5.1 5.0 4.5 4.4 5.0 5.1 4.8 5.1 4.6 5.3 5.0 7.0 6.4 6.9 5.5
## [55] 6.5 5.7 6.3 4.9 6.6 5.2 5.0 5.9 6.0 6.1 5.6 6.7 5.6 5.8 6.2 5.6 5.9 6.1
## [73] 6.3 6.1 6.4 6.6 6.8 6.7 6.0 5.7 5.5 5.5 5.8 6.0 5.4 6.0 6.7 6.3 5.6 5.5
## [91] 5.5 6.1 5.8 5.0 5.6 5.7 5.7 6.2 5.1 5.7 6.3 5.8 7.1 6.3 6.5 7.6 4.9 7.3
## [109] 6.7 7.2 6.5 6.4 6.8 5.7 5.8 6.4 6.5 7.7 7.7 6.0 6.9 5.6 7.7 6.3 6.7 7.2
## [127] 6.2 6.1 6.4 7.2 7.4 7.9 6.4 6.3 6.1 7.7 6.3 6.4 6.0 6.9 6.7 6.9 5.8 6.8
## [145] 6.7 6.7 6.3 6.5 6.2 5.9#`r mean(ir$Sepal.Lenth)`#remotes::install_github(“hadley/emo”, force = TRUE)
knitr::kable(ir[1:18, ])| X | Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
|---|---|---|---|---|---|
| 1 | 5.1 | 3.5 | 1.4 | 0.2 | setosa |
| 2 | 4.9 | 3.0 | 1.4 | 0.2 | setosa |
| 3 | 4.7 | 3.2 | 1.3 | 0.2 | setosa |
| 4 | 4.6 | 3.1 | 1.5 | 0.2 | setosa |
| 5 | 5.0 | 3.6 | 1.4 | 0.2 | setosa |
| 6 | 5.4 | 3.9 | 1.7 | 0.4 | setosa |
| 7 | 4.6 | 3.4 | 1.4 | 0.3 | setosa |
| 8 | 5.0 | 3.4 | 1.5 | 0.2 | setosa |
| 9 | 4.4 | 2.9 | 1.4 | 0.2 | setosa |
| 10 | 4.9 | 3.1 | 1.5 | 0.1 | setosa |
| 11 | 5.4 | 3.7 | 1.5 | 0.2 | setosa |
| 12 | 4.8 | 3.4 | 1.6 | 0.2 | setosa |
| 13 | 4.8 | 3.0 | 1.4 | 0.1 | setosa |
| 14 | 4.3 | 3.0 | 1.1 | 0.1 | setosa |
| 15 | 5.8 | 4.0 | 1.2 | 0.2 | setosa |
| 16 | 5.7 | 4.4 | 1.5 | 0.4 | setosa |
| 17 | 5.4 | 3.9 | 1.3 | 0.4 | setosa |
| 18 | 5.1 | 3.5 | 1.4 | 0.3 | setosa |
PAQUETE LEAFLET
library(leaflet)
ll_map <- leaflet()
ll_map <- addTiles(map = ll_map)
ll_map <-
setView(
map = ll_map,
lat = 13.527448,
lng = -89.057245,
zoom = 13
)
addPopups(
map = ll_map,
lat = 13.527448,
lng = -89.057245,
popup = 'El Salvador'
)