geom_col

geom_col() creates bar charts where the heights of the bars represent values in the data. Unlike geom_bar(), which counts the number of cases, geom_col() displays the actual data values. This makes it useful for showing pre-summarized data such as means, totals, or other statistics.

Arguments

• plot::GGPlot (optional): a plot object to add this geom to. This is typically used to facilitate creating your ggplot as part of a @chain.
• data (DataFrame): Data to use for this geom. If not provided, the geom will inherit the data from ggplot.
• aes(...): the names of the columns in the DataFrame that will be used in the mapping
• inherit_aes: should the geom inherit aes from the ggplot?
• ...: options that are not mapped to a column (passed to Makie.BarPlot)

Stacking and Dodging

By default, multiple bars at the same position are stacked on top of each other. You can change this behavior with the position argument. Use position="dodge" to place bars side-by-side. When using position="dodge", bars will be grouped by the fill, color, group, or dodge aesthetic (checked in that order).

When to Use geomcol vs geombar

• Use geom_bar() when you want to count the number of observations in each category (the data is unsummarized)
• Use geom_col() when you have pre-computed values you want to display (the data is already summarized)

Required Aesthetics

• x - the categorical variable
• y - the numeric value to display as bar height

Optional Aesthetics (see aes)

• fill (maps to bar interior color)
• color / colour (maps to bar outline color)
• dodge (grouping variable for side-by-side bars)
• group (grouping variable)

Optional Arguments

• position: "stack" (default) or "dodge"
• color / colour
• stroke / strokewidth
• strokecolor / strokecolour
• direction: :y (default) or :x
• dodge_gap: gap between dodged bars
• gap: gap between bar groups
• alpha

using TidierPlots
using TidierData
using DataFrames

penguins = penguins_data();

First, we create a summarized dataset with mean bill length by species and sex:

df = @chain penguins begin
    @group_by(species, sex)
    @summarize(mean_bill_length_mm = mean(bill_length_mm))
    @ungroup()
end

6×3 DataFrame

Row	species	sex	mean_bill_length_mm
	String	String	Float64
1	Adelie	male	40.3904
2	Adelie	female	37.2575
3	Gentoo	female	45.5638
4	Gentoo	male	49.4738
5	Chinstrap	female	46.5735
6	Chinstrap	male	51.0941

Basic bar chart showing pre-computed values:

ggplot(df, @aes(x = species, y = mean_bill_length_mm)) +
    geom_col()

Use the fill aesthetic to color bars by a grouping variable. Bars are stacked by default:

ggplot(df, @aes(x = species, y = mean_bill_length_mm, fill = sex)) +
    geom_col()

Use position="dodge" with the group aesthetic to place bars side-by-side:

ggplot(df, @aes(x = species, y = mean_bill_length_mm, group = sex)) +
    geom_col(position = "dodge")

You can also use the dodge aesthetic directly:

ggplot(df, @aes(x = species, y = mean_bill_length_mm, dodge = sex)) +
    geom_col()

Combine fill with position dodge for colored side-by-side bars:

ggplot(df, @aes(x = species, y = mean_bill_length_mm, fill = sex, dodge = sex)) +
    geom_col()

Customize appearance with stroke and transparency:

ggplot(df, @aes(x = species, y = mean_bill_length_mm, fill = sex)) +
    geom_col(strokecolor = :black, strokewidth = 1, alpha = 0.8, position = "dodge")

Create horizontal bars by using direction = :x:

df_single = @chain penguins begin
    @group_by(species)
    @summarize(mean_bill_length_mm = mean(bill_length_mm))
end

ggplot(df_single, @aes(x = species, y = mean_bill_length_mm)) +
    geom_col(direction = :x)

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