ggplot2_cheatsheet_group16.Rmd

# ggplot2 cheatsheet

Haoyuan Sun, Zhongtian Qiao

```{r, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE)
```

```{r}
library(tidyverse)
library(ggplot2)
```


## Overview
ggplot2 is a system for declaratively creating graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. This cheatsheet shows code options for commonly used graphs by using ggplot2.

## scatter plot

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy))
```

We can get a scatter plot by using `geom_point()`.

### Setting color

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy), color = "blue")
```

We can change the color of the poionts by using `color =`. 

### Color by groups

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy, color = class))
```

If X-variable is a categorical variable, such as variable "class", we can set points of different classes to have different colors.

### Identify overlapping points

```{r}
ggplot(data = mpg) +
  geom_count(aes(x = displ, y = hwy))
```

We can get a scatter plot by using `geom_count`. The size of the points shows if the point is overlap.

## Line plot

```{r}
ggplot(data = mpg) +
  geom_line(aes(x = displ, y = hwy))
```

We can get a line plot by using `geom_line()`.

~ Use `lty =` to change the type of line.
~ Use `size =` to change the size of line.
~ Use `col =` to change the color of line.

### Adding an arbitrary line

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy)) +
  geom_abline(slope = 1, intercept = 20)
```

We can add arbitrary lines by using `geom_abline()`.

## Box plot

```{r}
ggplot(data = mpg) +
  geom_boxplot(aes(x = class, y = hwy))
```

We can get a box plot by using `geom_boxplot()`.

### Horizontal box plot 
```{r}
ggplot(data = mpg) +
  geom_boxplot(aes(x = class, y = hwy)) +
  coord_flip()
```

By using `coord_flip()`, we will get a horizontal box plot.

## Histogram

```{r}
ggplot(data = mpg) +
  geom_histogram(aes(x = hwy))
```

We can get a histogram by using `geom_histogram()`.

### Bins

```{r}
ggplot(data = mpg) +
  geom_histogram(aes(x = hwy), bins = 10)
```

The default value of bin is 30. By changing the value of `bins =`, we can get different width of bin.

## Bar plot

```{r}
ggplot(data = mpg, aes(x = hwy, y = displ)) +
  geom_bar(position = "dodge", stat = "identity")
```

We can get a barplot which shows the relationship between of hwy and displ by using `geom_bar` with arguments `position="dodge"` and `stat = "identity"`. 

## Heatmap

```{r}
x <- c(1, 1, 1, 2, 2, 2, 3, 3, 3)
y <- c(1, 2, 3, 1, 2, 3, 1, 2, 3)
df <- data.frame(x, y)
set.seed(2017)
df$z <- sample(9)
ggplot(df, aes(x, y)) +
  geom_raster(aes(fill = z))
```

### Another way to plot heatmap

```{r}
ggplot(df, aes(x, y, fill = z)) +
  geom_tile() 
```

## Countour plot

```{r}
ggplot(data = mpg, aes(x = displ, y = hwy)) +
  geom_density2d() +
  geom_point(size = 1, alpha = 0.3)
```

We can get a contour plot by using `geom_density2d()`.

## Area plot 

```{r}
ggplot(data = economics) +
  geom_area(aes(x = date, y = unemploy))
```

If we want to analyse 2 continuous variables, we can plot an area plot by using `geom_area`.

## Adding Text 

### title and xy-corrdinate
```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy, color = class)) +
  labs(title = "displ v.s. hwy",
       subtitle = "group by different class",
       x = "Displ",
       y = "Hwy",
       color = "Class")

```

By using `labs()`, we can add more information for the plot, such as the title, subtitle, x-coordinate, y-coordinate, the class of color, the class of fill, etc.

### Label

```{r}
data <- data.frame(name = c("a", "b", "c"), count = c(20, 10, 30))

ggplot(data, aes(name, count)) +
  geom_bar(stat = "identity") +
  geom_text(aes(label = count))
```

We can get the label for the plot of data by `geom_text()`, 

~ The content of label is controlled by `aes(label = )`.
~ Use `hjust` and `vjust` to adjust the vertical and horizontal position of the label. 
~ Use `col = ` to adjust the color of the label. 
~ Use `size = ` to adjust the size of the label. 

```{r}
ggplot(data, aes(name, count)) +
  geom_bar(stat = "identity") +
  geom_text(aes(label = count), col = "blue", vjust = -0.3, size = 5)
```

## Facet

### facet_wrap

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy)) +
  facet_wrap(~class,nrow=2)
```

We can get multiple plots group by class by using `facet_wrap`.

### facet_grid

```{r}
ggplot(data = mpg) +
  geom_point(aes(x = displ, y = hwy)) +
  facet_grid(drv~cyl)
```

We can get multiple plots which are group by drv and cyl by using `facet_grid`.