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| Original file line number | Diff line number | Diff line change |
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| --- | ||
| title: Code Handout - Data Visualisation with ggplot2 | ||
| output: | ||
| html_document: | ||
| df_print: paged | ||
| code_download: yes | ||
| --- | ||
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| This document contains all of the functions that we have covered thus far in the | ||
| course. It will be updated every week, after we've added new skills. Each | ||
| function is presented alongside an example of how it is used. | ||
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| All of the examples below are in the context of the Palmer Penguins, found | ||
| [here (link)](https://allisonhorst.github.io/palmerpenguins/index.html). | ||
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| ## Foundations of `ggplot()` | ||
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| - `ggplot()` -- a function to create the shell of a visualization, where | ||
| specific variables are mapped to different aspects of the plot | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) | ||
| ``` | ||
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| - `aes()` -- aesthetics that can be used when creating a `ggplot()`, where the | ||
| aesthetics can either be hard coded (e.g. `color = "blue"`) or associated with | ||
| a variable (e.g. `color = sex`). | ||
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| - The following are the aesthetic options for *most* plots: | ||
| - `x` | ||
| - `y` | ||
| - `alpha` -- changes transparency | ||
| - `color` -- produces colored outline | ||
| - `fill` -- fills with color | ||
| - `group` -- used with categorical variables, similar to color | ||
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| - **`+`** -- an important aspect creating a `ggplot()` is to note that the | ||
| `geom_XXX()` function is separated from the `ggplot()` function with a plus | ||
| sign, `+`. | ||
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| - `ggplot()` plots are constructed in series of layers, where the plus sign | ||
| separates these layers. | ||
| - Generally, the `+` sign can be thought of as the end of a line, so you | ||
| should always hit enter/return after it. While it is not mandatory to move | ||
| to the next line for each layer, doing so makes the code a lot easier to | ||
| organize and read. | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() | ||
| ``` | ||
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| ## Geometric Objects to Visualize the Data | ||
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| - `geom_histogram( )` -- adds a histogram to the plot, | ||
| where the observations are binned into ranges of values and then frequencies | ||
| of observations are plotted on the y-axis | ||
| - You can specify the number of bins you want with the `bins` argument | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm)) + | ||
| geom_histogram(bins = 20) | ||
| ``` | ||
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| - `geom_boxplot( )` -- adds a boxplot to the plot, where observations are | ||
| aggregated (summarized), the min, Q1, median, Q3, and maximum are plotted as the | ||
| box and whiskers, and "outliers" are plotted as points. | ||
| - You can plot a vertical boxplot by specifying the `x` variable, or a | ||
| horizontal boxplot by specifying the `y` variable. | ||
| - Note: the min and max may not be included in the whiskers, if they are | ||
| deemed to be "outliers" based on the $1.5 \\times \\text{IQR}$ rule. | ||
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| ```r | ||
| ## Horizontal boxplot | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm)) + | ||
| geom_boxplot() | ||
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| ## Vertical boxplot | ||
| penguins %>% | ||
| ggplot(aes(y = bill_length_mm)) + | ||
| geom_boxplot() | ||
| ``` | ||
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| - `geom_density()` -- adds a density curve to the plot, where the probability | ||
| density is plotted on the y-axis (so the density curve has a total area of one). | ||
| - By default this creates a density curve without shading. By specifying a | ||
| color in the `fill` argument, the density curve is shaded. | ||
| - Can be thought of as the "one group" violin plot! | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm)) + | ||
| geom_density(fill = "tomato") | ||
| ``` | ||
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| - `geom_violin()` -- plots violins for each level of a categorical variable | ||
| - Can be thought of as a hybrid mix of `geom_boxplot()` and `geom_density()`, | ||
| as the density is displayed, but it is reflected to provide a plot similar in | ||
| nature to a boxplot. | ||
| - To obtain violins stacked vertically, declare the categorical variable as `y`. | ||
| To obtain side-by-side violins, declare the categorical variable as `x`. | ||
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| ```r | ||
| ## Stacked vertically | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = species)) + | ||
| geom_violin() | ||
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| ## Side-by-side | ||
| penguins %>% | ||
| ggplot(aes(y = bill_length_mm, x = species)) + | ||
| geom_violin() | ||
| ``` | ||
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| - `geom_bar()` -- creates a barchart of a categorical variable | ||
| - Can produce stacked barcharts by specifying a variable as the `fill` | ||
| aesthetic. | ||
| - Can change from stacked barchart to a side-by-side barchart by specifying | ||
| `position = "dodge"`. | ||
| - If your data are already in counts (e.g. output from `count()`), then you | ||
| can specify the `stat = "identity"` argument inside `geom_bar()`. | ||
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| ```r | ||
| ## Stacked barchart | ||
| penguins %>% | ||
| ggplot(aes(x = species)) + | ||
| geom_bar(aes(fill = sex)) | ||
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| ## Side-by-side barchart | ||
| penguins %>% | ||
| ggplot(aes(x = species)) + | ||
| geom_bar(aes(fill = sex), | ||
| position = "dodge") | ||
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| ## If data are raw counts | ||
| penguins %>% | ||
| count(species, sex) %>% | ||
| ggplot(aes(x = species, y = n)) + | ||
| geom_bar(aes(fill = sex), | ||
| stat = "identity", | ||
| position = "dodge") | ||
| ``` | ||
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| - `geom_point()` -- plots each observation as an (x, y) point, used to create | ||
| scatterplots | ||
| - Can use `alpha` to increase the transparency of the points, to reduce | ||
| overplotting. | ||
| - Can specify `aes`thetics inside of `geom_point()` for local aesthetics (point | ||
| level) or inside of `ggplot()` for global aesthetics (plot level) | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm)) + | ||
| geom_point(aes(color = species)) | ||
| ``` | ||
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| - `geom_jitter()` -- plots each observation as an (x, y) point and adds a small | ||
| amount of jitter around the point | ||
| - Useful so that we can see each point in the locations where there are | ||
| overlapping points. | ||
| - Can specify the `width` and `height` of the jittering using the optional | ||
| arguments. | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(y = body_mass_g, x = species)) + | ||
| geom_violin() + | ||
| geom_jitter(aes(color = sex), width = 0.25, height = 0.25) | ||
| ``` | ||
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| - `geom_smooth()` -- plots a line over a set of points, draws the readers eye | ||
| to a specific trend | ||
| - The methods we will use are "lm" for a linear model (straight line), and | ||
| "loess" for a wiggly line | ||
| - By default, the smoother gives you gray SE bars, to remove these add | ||
| `se = FALSE` | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") | ||
| ``` | ||
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| - `facet_wrap()` -- creates subplots of your original plot, based on the levels | ||
| of the variable you input | ||
| - To facet by one variable, use `~variable`. | ||
| - To facet by two variables, use `variable1 ~ variable2`. | ||
| - If you prefer for your facets to be organized in rows or columns, use the | ||
| `nrow` and/or `ncol` arguments. | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") + | ||
| facet_wrap(~island, nrow = 1) | ||
| ``` | ||
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| ## Plot Characteristics | ||
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| - `labs()` -- specifies the plot labels, possible labels are: x, y, color, fill, | ||
| title, and subtitle | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") + | ||
| labs(x = "Bill Length (mm)", | ||
| y = "Bill Depth (mm)", | ||
| color = "Penguin Species") | ||
| ``` | ||
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| - `theme_bw()` -- changes the plotting background to the classic dark-on-light | ||
| ggplot2 theme. | ||
| - This theme may work better for presentations displayed with a projector. | ||
| - Other theme options are `theme_minimal()`, `theme_light()`, and `theme_void()`. | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") + | ||
| labs(x = "Bill Length (mm)", | ||
| y = "Bill Depth (mm)", | ||
| color = "Penguin Species") + | ||
| theme_bw() | ||
| ``` | ||
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| - `theme()` -- | ||
| - Possible options are: | ||
| - `panel.grid` -- controls the grid lines (`panel.grid = element_blank()` | ||
| removes grid lines) | ||
| - `text` -- specifies font size for the entire plot (e.g. | ||
| `text = element_text(size = 16)` | ||
| - `axis.text.x` -- specifies the font size for the x-axis text | ||
| - `axis.text.y` -- specifies the font size for the y-axis text | ||
| - `plot.title` -- specifies aspects of the plot title, can use | ||
| `plot.title = element_text(hjust = 0.5)` to centre the title | ||
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| ```r | ||
| penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") + | ||
| labs(x = "Bill Length (mm)", | ||
| y = "Bill Depth (mm)", | ||
| color = "Penguin Species") + | ||
| theme_bw() + | ||
| theme(axis.text.x = element_text(size = 12), | ||
| axis.text.y = element_text(size = 12)) | ||
| ``` | ||
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| ## Exporting Plots | ||
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| - `ggsave()` -- convenient function for saving a plot | ||
| - Unless specified, defaults to the last plot that was made. | ||
| - Uses the size of the current graphics device to determine the size of the | ||
| plot. | ||
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| ```r | ||
| plot1 <- penguins %>% | ||
| ggplot(aes(x = bill_length_mm, y = bill_depth_mm, color = species)) + | ||
| geom_point() + | ||
| geom_smooth(method = "lm") + | ||
| facet_wrap(~island, nrow = 1) | ||
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| ggsave(path = "images/faceted_plot.png", plot = plot1) | ||
| ``` | ||
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