# The Grammar of Graphics with ggplot2 — R Programming

Source: https://www.geekswithgeeks.com/en/r-programming/v-ggplot

> Build plots from data, aesthetics and geoms with ggplot2.

## Plots built in layers

**ggplot2** implements the **grammar of graphics**: every plot combines **data**, **aesthetic mappings** (`aes()`) that connect variables to visual properties such as x, y, colour, size and fill, and **geoms** (geometric objects) that draw them: `geom_point()` for scatter plots, `geom_line()` for trends, `geom_col()` for bars with given heights, `geom_bar()` to count rows, `geom_histogram()` and `geom_density()` for distributions, `geom_boxplot()` for comparing groups, and `geom_smooth()` for trend lines. You build a plot by **adding layers** with `+`. Mappings inside `aes()` depend on data (`colour = city`), while settings outside `aes()` are fixed (`colour = "steelblue"`). Statistical transformations, scales and coordinate systems are further layers. The same small vocabulary produces almost any statistical chart, and plots are objects you can store, modify and save with `ggsave()`.

## Layers of a ggplot

Data, aesthetic mappings and geoms stack up into a complete plot.

![Three translucent stacked sheets: a grid of points, coloured markers and axis labels, combining into one chart.](assets/figures/r-programming/section-5-map.svg) — Figure 5.1 — The layered grammar of graphics.

## Three common plots

Scatter with trend, grouped bars and a distribution.

```r
library(ggplot2)
library(dplyr)

# scatter plot with a trend line per city
ggplot(sales, aes(x = order_date, y = amount_inr, colour = city)) +
  geom_point(alpha = 0.5) +
  geom_smooth(method = "loess", se = FALSE)

# revenue per city as bars
sales |>
  summarise(revenue = sum(amount_inr), .by = city) |>
  ggplot(aes(x = reorder(city, revenue), y = revenue)) +
  geom_col(fill = "steelblue") +
  coord_flip()

# distribution of order values, log scale for skewed money data
ggplot(sales, aes(x = amount_inr)) +
  geom_histogram(bins = 30) +
  scale_x_log10()

ggsave("figures/order_values.png", width = 7, height = 4, dpi = 300)
```

## Inside or outside aes?

`aes(colour = "blue")` maps a constant string as if it were data, giving a legend called "blue" and an unexpected colour. Set fixed colours outside `aes()`: `geom_point(colour = "blue")`.

**Quiz:** In ggplot2, what does aes() define?

- [x] Mappings from data variables to visual properties such as x, y and colour
- [ ] The file format of the plot
- [ ] The theme only
- [ ] The number of bins

*Answer:* Mappings from data variables to visual properties such as x, y and colour. Aesthetic mappings connect data columns to visual channels.