Elaboração de mapas de distribuição de espécies em R

# .midlarge[.black[Elaboração de mapas de distribuição de espécies em R]]

## .mid[.black[Comandos básicos para você preparar seu próprio mapa]]

#### .large[.black[Dr. Ricardo Perdiz | 21--22 Out 2021 | Dia 01]]

]

.center[
<img src="./figuras/logo_principal_com_fundo.png" style="width:125px;height:125px;">
]
<img src="./figuras/mapa_slide.png" style="width:560px;height:480px;">

]

<div class="cr cr-top cr-left cr-sticky cr-black">COVID19</div>

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<div class="cr cr-top cr-left cr-sticky cr-black">COVID19</div>

---

class: middle, center, hide_logo
background-image: url("figuras/who-am-i.001.jpeg")
background-size: cover

### Sobre mim

**Dr. em Botânica (INPA)**  
  **Analista de dados**  
  
  [<svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg">  <path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg> @ricoperdiz](https://github.com/ricoperdiz)  
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]

???

Meu nome é Ricardo de Oliveira Perdiz. 
Sou um biólogo com mestrado e doutorado em botânica, minha linha de pesquisa é com a evolução e sistemática da flora Neotropical, em especial a família do palo santo, mirra, breus, e amesclas, conhecida pelo nome científico Burseraceae. Também me dedico à criação de ferramentas para facilitar a análise de dados taxonômicos e produção de monografias taxonômicas.

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<div class="cr cr-top cr-left cr-sticky cr-black">COVID19</div>

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# Sumário de hoje

## [Introdução](#introducao) básica ao R

## Tutorial para elaborar o mapa

### Carregar [pacotes](#pacotes)

### Importar [dados](#dados)

### Checagem e limpeza de [dados](#limpeza)

### Criação de [variáveis](#variaveis)

---

## Versão simplificada do tutorial [Obtendo dados e plotando mapas no R ](https://www.ricardoperdiz.com/blog/2020-03-obtendo-dados-e-plotando-mapas-no-r-versão-3/)

### Carregar [pacotes](#pacotes)

### Importar [dados](#dados)

### .red[[Checagem e limpeza de dados](https://www.ricardoperdiz.com/blog/2020-03-obtendo-dados-e-plotando-mapas-no-r-versão-3/)]

### Criação de [variáveis](#variaveis)

### [Plota](https://minicurso-elaboracao-mapa-r-dia02.netlify.app/#14) o mapa

???

Apresentarei uma versão simplificada do tutorial, SEM A CHECAGEM e LIMPEZA dos DADOS (RISCAR ESSA PARTE).

Essa parte amanhã será explorada no dia 2 do minicurso.

---
name: introducao
class: inverse, center, middle
# Introdução básica

![R](figuras/R.png)

???

Desejo agora explanar brevemente sobre o que é o R, e passar conhecimentos bem simplificados que são necessários para manipulação de dados em ambiente R.

---

## O que é o R?

> **R** é uma **linguagem** e **ambiente** para análise estatística e produção de gráficos de alta qualidade.

---

## O que é o R?

> **R** pode ser utilizado para manipular e analisar dados, criar gráficos, e simulação computacional.

---

## O que é o R?

> **R** pode ter extensão de funções através do uso de **[pacotes](https://www.cran.r-project.org/web/packages/)**, baixados por meio do **C**omprehensive **R** **A**rchive **N**etwork (**[CRAN](https://www.cran.r-project.org))**

---

## Por que usar o R???

#### 1. É grátis

#### 2. Gráficos excelentes

#### 3. Diversidade de ferramentas (=pacotes) para fazer análises estatísticas

#### 4. Liberdade para criação de funções

---

### Como obter o R?

Visitar a página do projeto: [www.r-project.org](www.r-project.org).

Verificar este tutorial para instalação: [https://github.com/ricoperdiz/minicurso-elaboracao-mapa-R/blob/main/extra-ref/Instrucoes_ROPerdiz_instalando_Baixando_R.pdf](https://github.com/ricoperdiz/minicurso-elaboracao-mapa-R/blob/main/extra-ref/Instrucoes_ROPerdiz_instalando_Baixando_R.pdf).

---

## Qual é a cara do R? Mac OS

![R no MAC OS X](figuras/01.png)

---

## Qual é a cara do R? Windows

![R no Windows](figuras/cara_R_windows.png)

---

## Como é a linguagem do R

> "*Orientada a objetos*" - *object-oriented programming*

![budasaid](figuras/budasaid.jpg)

---

## Como é a linguagem do R

* Escrever em R é como escrever em português, inglês etc;

* Programar em linguagens como R consiste em definir *funções* e *variáveis*;

* *Variáveis* podem ser números ou palavras; guardamos esses valores para uso posterior;

* *Funções* executam comandos, por meio de *argumentos*;

* Comandos geram resultados.

---

## R é calculadora!

```r
1 + 1
```

```
## [1] 2
```

```r
resultado <- 22*3^2
77*resultado
```

```
## [1] 15246
```

---

### Variáveis

Variáveis em R são assinaladas utilizando a notação ` <- `.

```r
meunome <- "Ricardo de Oliveira Perdiz"
idade <- 17
paste(meunome, "tem", idade, "anos")
```

```
## [1] "Ricardo de Oliveira Perdiz tem 17 anos"
```

---

### Mais exemplos

```r
> string <- 'Olá, Itacoatiara!'
> meu_numero <- 25
```
]

```r
> string
```

```
## [1] "Olá, Itacoatiara!"
```

```r
> meu_numero
```

```
## [1] 25
```
]

```r
> print(string)
```

```
## [1] "Olá, Itacoatiara!"
```

```r
> print(meu_numero)
```

```
## [1] 25
```
]
]

---

### Funções e argumentos

* **Função** -> é um elemento em R que requer uma ação do computador. Cumpre determinada tarefa.

* **Argumento** -> especifica ou modifica como uma função trabalha. É especificado dentro de "parênteses" após o nome da função

```r
> seq(from = 0,to = 10,by =1)
```

```
##  [1]  0  1  2  3  4  5  6  7  8  9 10
```

---

### Como é a linguagem do R

##### Anatomia de uma linha de comando

```r
> x <- sample(1:10,20,replace=TRUE)
```

]

```r
> x <- sample(1:10, 20, replace = TRUE)
```

]

```r
> print(x)
```

```
##  [1]  5  4  5  6  2  3  8  1  8  7 10  7  5  6  6  2  1 10  2  3
```

]

```r
> mean(x)
```

```
## [1] 5.05
```

]

---

### Detalhes *nomenclaturais* em R

* Separador de decimal é ponto (= "."); vírgula separa **argumentos**

* O símbolo de *igual* "=" atribui valores aos **argumentos**

* Nomes de **argumentos** podem ser omitidos, desde que os valores estejam seguindo a ordem pré-determinada da função. Ver o '?help'

* Aspas guardam texto; parênteses servem para abrir e fechar funções ou vetores; nomes de objetos não podem ter espaços nem símbolos especiais.

---

### O meu melhor amigo é o **?** (ou a ajuda do R!)

Ter dúvidas é comum ao programar.

O R possui um excelente recurso, o `?` (ajuda, ou "help").

Uma das maneiras é digitar "?" + "*nomeDaFunção*".

```r
?seq
```

---

### O meu melhor amigo é o **?** (ou a ajuda do R!)

![helpseq](figuras/seq.png)

---

### Viva o poder da linguagem R

.panelset.sideways[
.panel[.panel-name[Gráfico 1]
![](index_files/figure-html/unnamed-chunk-15-1.png)
]

![](index_files/figure-html/unnamed-chunk-16-1.png)
]

![](index_files/figure-html/unnamed-chunk-17-1.png)

]

.panel[.panel-name[Mapas em R com `tmaps`]
![](index_files/figure-html/unnamed-chunk-18-1.png)
]

![](figuras/itacoa.png)

]

---

## Recursos para aprender a linguagem **R**

#### [Curso básico de introdução à linguagem R](https://intror.netlify.app)

![Curso R](figuras/cursoR.png)

---

## Recursos para aprender linguagens de programação - [Grasshopper](https://grasshopper.app/pt_br/)

![grasshopper](figuras/grasshopper.png)

---
class: inverse, center, middle

## Mais recursos???

### Buscar, sempre! Google, Yahoo, etc.

---

### [R-bloggers](https://www.r-bloggers.com/)

![R bloggers](figuras/rbloggers.png)

---

## Minicurso baseado na postagem abaixo:

[Obtendo dados e plotando mapas no R ](https://www.ricardoperdiz.com/blog/2020-03-obtendo-dados-e-plotando-mapas-no-r-versão-3/)

![Postagem](figuras/postagem.png)

???

O tutorial é bem simples e visa a produção de um mapa de distribuição geográfica utilizando dados que abrangem a distribuição espacial de duas espécies de _[Burseraceae](https://en.wikipedia.org/wiki/Burseraceae)_, _Protium aracouchini_ (Aubl.) Marchand e _P. heptaphyllum_ (Aubl.) Marchand.  A primeira planta faz parte de um complexo de espécies informalmente denominado complexo _Protium aracouchini_, cuja sistemática e taxonomia vem sendo objeto de estudo em [meu doutorado](http://www.botanicaamazonica.wiki.br/labotam/doku.php?id=alunos:r.perdiz:projeto:inicio). A segunda espécie, _P. heptaphyllum_, é objeto de estudo de [Gabriel Damasco](https://ib.berkeley.edu/labs/fine/Site/Gabriel.html), colaborador do LABOTAM e aluno de doutorado na Universidade da Califórnia, Berkeley.

Os dados foram baixados do [herbário virtual do Jardim Botânico de Nova Iorque](http://sweetgum.nybg.org/science/vh/) que é onde trabalha o especialista em Burseraceae, Dr. Douglas Daly, e cuja coleção de espécimes e dados vêm sendo bem cuidada há algumas décadas. Para esta postagem, filtramos apenas os dados para as duas espécies citadas acima.

---

## Assuntos abordados

* (Instalar e) Carregar pacotes

* Importação de dados

* Checagem de dados

* Criação de variáveis

* Plotagem do mapa

---

## Instalando pacotes

```r
install.packages("maps")
```

![Instalando pacotes](figuras/instalando_pacotes.png)

---
name: pacotes
## Carregando os pacotes

```r
library("maps")
```

???

A postagem original faz uso dos pacotes maps (para plotar o mapa), RColorBrewer (paleta de cores), magrittr (pipe, ou `%>%`) e dplyr (manipulação de 'dataframes').

Neste minicurso, utilizaremos apenas o pacote `maps`, a fim de simplificar o aprendizado.

---

### Intervalo

!['coffeandcode'](figuras/coffeCode.jpg)

---
name: dados
## Importando os dados

Os dados estão reunidos em um arquivo chamado `dados.csv`, disponível em: [https://github.com/ricoperdiz/Tutorials/blob/master/R_make_a_map/dados.csv](https://github.com/ricoperdiz/Tutorials/blob/master/R_make_a_map/dados.csv).

As informações estão separadas por tabulação e codificadas em UTF-8.

Você pode baixar os dados direto da página do GitHub ou fazer uso do comando abaixo para ler diretamente os dados da rede.

```r
protium <-
  read.table(
    file = url(
      "https://raw.githubusercontent.com/ricoperdiz/Tutorials/master/R_make_a_map/dados.csv"
    ),
    header = TRUE,
    as.is = TRUE,
    sep = '\t',
    dec = '.'
  )
```

---

## Destrinchando o `read.table`

> read.table() - Função básica para ler arquivos no R

### Argumentos

> file - Local do arquivo

> header - Tem cabeçalho ou não?

> as.is - Classes dos vetores. Deixa como está ou faz alguma conversão?

> sep - Separador de texto.

> dec - Separador de decimal.

---

## Checagem inicial dos dados

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---
name: limpeza
class: inverse, middle, center
## Checagem e limpeza dos dados

### Existência de valores vazios; em caso positivo, devemos eliminá-los;

### Confiabilidade dos valores de latitude e longitude

### Valores duplicados?

???

Há valores vazios?  
Dados de Latitude e latitude, às vezes, por diversos fatores, há troca de sinais (negativos e positivos) ocasionando equívocos quanto à ocorrência exata da amostra. Se for percebido algo assim, é bom checar os dados e buscar corrigí-los.
Há valores duplicados?

---

## Um pouco de classe de objetos

Nossa tabela, após a importação, é chamada de `data.frame`.

```r
class(protium)
```

```
## [1] "data.frame"
```

```r
dim(protium)
```

```
## [1] 667   8
```

---

## Acessando vetores em (ou partes de) um `data.frame`

> Utilizamos o "$"

```r
head(protium$recordedBy)
```

```
## [1] "A_A_de_Oliveira" "A_B_Anderson"    "A_C_Londoño"    
## [4] "A_C_Londoño"     "A_C_Weber"       "A_Castillo"
```

---

## Acessando vetores em (ou partes de) um `data.frame`

> Ou então colchetes, com o nome da coluna dentro de aspas, dentro dos colchetes

```r
head(protium[, "recordedBy"])
```

```
## [1] "A_A_de_Oliveira" "A_B_Anderson"    "A_C_Londoño"    
## [4] "A_C_Londoño"     "A_C_Weber"       "A_Castillo"
```

---

## Cria variáveis para plotar o mapa

### Nomes de espécies

```r
unique(protium$Species)
```

```
## [1] "Protium aracouchini"  "Protium heptaphyllum"
```

```r
spp <- unique(protium$Species)
spp
```

```
## [1] "Protium aracouchini"  "Protium heptaphyllum"
```

---

### Variáveis - Vetor de cores para utilizar no mapa

Para cada espécie, uma cor!

Vamos conhecer o famoso "if else", ou em português:

> Se ..., caso contrário ...

```r
head(ifelse(protium$Species == spp[1], 'red','black'), 50)
```

```
##  [1] "red"   "black" "red"   "red"   "red"   "black" "black" "black"
##  [9] "black" "black" "black" "black" "black" "red"   "red"   "red"  
## [17] "red"   "black" "black" "red"   "red"   "red"   "black" "red"  
## [25] "black" "red"   "black" "black" "red"   "red"   "red"   "black"
## [33] "red"   "red"   "black" "red"   "red"   "red"   "red"   "black"
## [41] "black" "black" "red"   "black" "black" "red"   "black" "black"
## [49] "red"   "black"
```

---

### Destrinchando o ifelse

```r
spp[1]
```

```
## [1] "Protium aracouchini"
```

```r
head(protium$Species == spp[1], 10)
```

```
##  [1]  TRUE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
```

---

### Variáveis - Vetor de cores para utilizar no mapa

Para cada espécie, uma cor!

```r
cores.map <- ifelse(protium$Species == spp[1], 'red','black')
head(cores.map, 50)
```

---

# Fim do dia 1!

## Amanhã, dia 22 de outubro, continuaremos!

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