---
title: "Cheat Sheet"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{cheat-sheet}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## Troubleshooting

When you don’t see any `>` at the bottom of your console, hitting escape
might help. If it doesn’t, clicking the stop sign in the top right
corner of the console might help.

You will be able to solve any other problem when you google it.

## Shortcuts

| Shortcut        | Result                        |
| --------------- | ----------------------------- |
| `Alt` + `-`     | `<-`                          |
| `Ctrl`+ `Enter` | Run selected code from Script |
| `Enter`         | Run line of code in Console   |

## Useful packages

  - dplyr
  - olsrr
  - ggplot2
  - vegan
  - betapart
  - FD

## Useful functions

### Packages

  - `install.packages()` - only needs to happen once
  - `library()` - needs to happen every session

### Loading data

  - `data()` - loading data from package
  - `read.csv()` - loading data form .csv file. If your data is not displayed as separate columns,
    explore the use of the `sep` and `dec` arguments.

### Examining objects

  - `class()`
  - `str()`
  - `length()`
  - `dim()`
  - `summary()`
  - `head()`
  - `tail()`
  - `names()` or `colnames()`
  - `ncol()`and `nrow()`
  - `levels()`

#### Checking for special values

  - `is.na()`
  - `anyNA()`
  - `is.nan()`
  - `is.infinite()`

### Creating objects

  - `c()`
  - `vector()`
  - `matrix()`
  - `list()`
  - `data.frame()`
  - `cbind()` and `rbind()`

### Selecting subsets of objects

When `a` is a data.frame

  - `a$plot` - selects the column from `a` which is called “plot”
  - `a[,"plot"]` - selects the column from `a` which is called “plot”
  - `a[1,2]` - selects the value at the first row, second column
  - `a[,2]` - selects the second column as a numeric vector
  - `a[1,]` - selects the first row as a numeric vector
  - `a[2]` - selects the second column as a data frame

### Visualisation

  - `plot()`
  - `points()`
  - `lines()`
  - `pairs()`
  - `hist()`
  - `boxplots()`
  - `par()`

### Iterating

  - `apply()`
  
### Diversity analysis
  
  - `specnumber()`
  - `diversity()`
  - `tsallis()`
  - `specpool()`
  - `specaccum()`
  - `betadiver()`
  - `beta.pair()`
  - `beta.multi()`