PRACTICA 01: INICIANDO EN R Y RSTUDIO
ELECTIVA II
IMPORTAR Y VERIFICAR DATOS
#Instalar un paquete
#install.packages("dplyr")
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
#Buscar espacio de trabajo
getwd()
## [1] "C:/Users/ASUS/Documents/TATI 2021-1/TRABAJOS R"
#Asignar espacio de trabajo
setwd("~/TATI 2021-1/TRABAJOS R")
edidiv <- read.csv("~/TATI 2021-1/TRABAJOS R/CC-RBasics-master/edidiv.csv")
#Buscar espacio de trabajo
getwd()
## [1] "C:/Users/ASUS/Documents/TATI 2021-1/TRABAJOS R"
#Asignar espacio de trabajo
setwd("~/TATI 2021-1/TRABAJOS R")
edidiv <- read.csv("~/TATI 2021-1/TRABAJOS R/CC-RBasics-master/edidiv.csv")
#Comprobando datos
head(edidiv)
## organisationName gridReference year taxonName
## 1 Joint Nature Conservation Committee NT265775 2000 Sterna hirundo
## 2 Joint Nature Conservation Committee NT235775 2000 Sterna hirundo
## 3 Joint Nature Conservation Committee NT235775 2000 Sterna paradisaea
## 4 British Trust for Ornithology NT27 2000 Branta canadensis
## 5 British Trust for Ornithology NT27 2000 Branta leucopsis
## 6 The Wildlife Information Centre NT27S 2001 Turdus merula
## taxonGroup
## 1 Bird
## 2 Bird
## 3 Bird
## 4 Bird
## 5 Bird
## 6 Bird
tail(edidiv)
## organisationName gridReference year
## 25679 The Mammal Society NT278745 2016
## 25680 The Mammal Society NT277724 2016
## 25681 The Mammal Society NT266728 2016
## 25682 The Mammal Society NT270728 2016
## 25683 The Mammal Society NT257762 2016
## 25684 People's Trust for Endangered Species NT2372 2016
## taxonName taxonGroup
## 25679 Sciurus carolinensis Mammal
## 25680 Capreolus capreolus Mammal
## 25681 Sciurus carolinensis Mammal
## 25682 Oryctolagus cuniculus Mammal
## 25683 Vulpes vulpes Mammal
## 25684 Erinaceus europaeus Mammal
str(edidiv)
## 'data.frame': 25684 obs. of 5 variables:
## $ organisationName: chr "Joint Nature Conservation Committee" "Joint Nature Conservation Committee" "Joint Nature Conservation Committee" "British Trust for Ornithology" ...
## $ gridReference : chr "NT265775" "NT235775" "NT235775" "NT27" ...
## $ year : int 2000 2000 2000 2000 2000 2001 2001 2001 2001 2001 ...
## $ taxonName : chr "Sterna hirundo" "Sterna hirundo" "Sterna paradisaea" "Branta canadensis" ...
## $ taxonGroup : chr "Bird" "Bird" "Bird" "Bird" ...
head(edidiv$taxonGroup)
## [1] "Bird" "Bird" "Bird" "Bird" "Bird" "Bird"
class(edidiv$taxonGroup)
## [1] "character"
edidiv$taxonGroup <- as.factor(edidiv$taxonGroup)
#Mas exploracion
dim(edidiv)
## [1] 25684 5
summary(edidiv)
## organisationName gridReference year taxonName
## Length:25684 Length:25684 Min. :2000 Length:25684
## Class :character Class :character 1st Qu.:2006 Class :character
## Mode :character Mode :character Median :2009 Mode :character
## Mean :2009
## 3rd Qu.:2011
## Max. :2016
##
## taxonGroup
## Butterfly :9670
## Bird :7366
## Flowering.Plants:2625
## Mollusc :2226
## Hymenopteran :1391
## Mammal : 960
## (Other) :1446
summary(edidiv$taxonGroup)
## Beetle Bird Butterfly Dragonfly
## 426 7366 9670 421
## Flowering.Plants Fungus Hymenopteran Lichen
## 2625 334 1391 140
## Liverwort Mammal Mollusc
## 125 960 2226
CALCULAR LA RIQUEZA DE LAS ESPECIES
Beetle <- filter(edidiv, taxonGroup == "Beetle")
Bird <- filter(edidiv, taxonGroup == "Bird")
Butterfly <- filter(edidiv, taxonGroup == "Butterfly")
Dragonfly <- filter(edidiv, taxonGroup == "Dragonfly")
Flowering.Plants <- filter(edidiv, taxonGroup == "Flowering.Plants")
Fungus <- filter(edidiv, taxonGroup == "Fungus")
Hymenopteran <- filter(edidiv, taxonGroup == "Hymenopteran")
Lichen <- filter(edidiv, taxonGroup == "Lichen")
Liverwort <- filter(edidiv, taxonGroup == "Liverwort")
Mammal <- filter(edidiv, taxonGroup == "Mammal")
Mollusc <- filter(edidiv, taxonGroup == "Mollusc")
#Numero de especies diferentes por grupo
a <- length(unique(Beetle$taxonName))
b <- length(unique(Bird$taxonName))
c <- length(unique(Butterfly$taxonName))
d <- length(unique(Dragonfly$taxonName))
e <- length(unique(Flowering.Plants$taxonName))
f <- length(unique(Fungus$taxonName))
g <- length(unique(Hymenopteran$taxonName))
h <- length(unique(Lichen$taxonName))
i <- length(unique(Liverwort$taxonName))
j <- length(unique(Mammal$taxonName))
k <- length(unique(Mollusc$taxonName))
#Combinar valores en un vector
biodiv <- c(a,b,c,d,e,f,g,h,i,j,k)
names(biodiv) <- c("Beetle",
"Bird",
"Butterfly",
"Dragonfly",
"Flowering.Plants",
"Fungus",
"Hymenopteran",
"Lichen",
"Liverwort",
"Mammal",
"Mollusc")
#Visalizar los graficos
barplot(biodiv)
#Corregir grafico
png("barplot.png", width=1600, height=600)
barplot(biodiv, xlab="Taxa", ylab="Number of species", ylim=c(0,600), cex.names= 1.5, cex.axis=1.5, cex.lab=1.5)
dev.off()
## png
## 2
MARCO DE DATOS
# Creando un objeto llamado "taxa" contiene todos los nombres taxa
taxa <- c("Beetle",
"Bird",
"Butterfly",
"Dragonfly",
"Flowering.Plants",
"Fungus",
"Hymenopteran",
"Lichen",
"Liverwort",
"Mammal",
"Mollusc")
# Convertir el objeto en una variable categorica
taxa_f <- factor(taxa)
# Combinar todos los valores para el número de especies en una variable llamada "richness"
richness <- c(a,b,c,d,e,f,g,h,i,j,k)
# Crear el marco de datos a partir de dos vectores
biodata <- data.frame(taxa_f, richness)
# Guardar el archivo
write.csv(biodata, file="biodata.csv")
# Especificar columnas
png("barplot2.png", width=1600, height=600)
barplot(biodata$richness, names.arg=c("Beetle",
"Bird",
"Butterfly",
"Dragonfly",
"Flowering.Plants",
"Fungus",
"Hymenopteran",
"Lichen",
"Liverwort",
"Mammal",
"Mollusc"),
xlab="Taxa", ylab="Number of species", ylim=c(0,600))
dev.off()
## png
## 2