API

Index¤

Reference - Exported functions¤

# TidierPlots.aes — Method.

aes(args...; kwargs...)

Details

TBD

source

# TidierPlots.geom_bar — Function.

geom_bar(aes(...), ...)
geom_bar(plot::GGPlot, aes(...), ...)

Represent the counts of a grouping variable as columns.

Details

The columns are stacked by default, and the behavior can be changed with the "position" argument. The position can either be "stack" or "dodge". If the argument is "dodge", then a a grouping variable will also need to be supplied to aes. Alternatively you can supply the grouping variable to dodge within the aesthetic.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.BarPlot)

Required Aesthetics

x OR y (not both)

Optional Aesthetics (see aes)

color / colour
strokecolor / strokecolour
dodge
group

Optional Arguments

position: "stack" (default) or "dodge"
stroke / strokewidth
strokecolor / strokecolour
direction: :y (default) or :x
dodge_gap
gap

Examples

# vertical bar plot
ggplot(penguins) + geom_bar(@aes(x = species))

# horizontal bar plot
ggplot(penguins) + geom_bar(@aes(y = species))

ggplot(penguins, @aes(x = species, color=sex, dodge=sex)) + geom_bar()

source

# TidierPlots.geom_boxplot — Function.

geom_boxplot(aes(...), ...)
geom_boxplot(plot::GGPlot, aes(...), ...)

Compactly displays the distribution of continuous data.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.BoxPlot)

Required Aesthetics

x (integer or categorical)
y (numeric)

Optional Aesthetics (see aes)

color / colour (used in conjunction with dodge)
dodge

Optional Arguments

orientation=:vertical: orientation of box (:vertical or :horizontal)
width=1
gap=0.2
show_notch=false
nothchwidth=0.5
show_median=true
dodge_gap=0.03

Examples

ggplot(penguins, @aes(x=species, y=bill_length_mm)) +
    geom_boxplot()

ggplot(penguins, @aes(x=species, y=bill_length_mm)) +
    geom_boxplot(orientation=:horizontal)

ggplot(penguins, @aes(x=species, y=bill_length_mm, dodge=sex, color=sex)) +
    geom_boxplot()

source

# TidierPlots.geom_col — Function.

geom_col(aes(...), ...)
geom_col(plot::GGPlot, aes(...), ...)

Represent data as columns.

Details

The columns are stacked by default, and the behavior can be changed with the "position" argument. The position can either be "stack" or "dodge". If the argument is "dodge", then a a grouping variable will also need to be supplied to aes. Alternatively you can supply the grouping variable to dodge within the aesthetic.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.BarPlot)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

color / colour
strokecolor / strokecolour
dodge
group

Optional Arguments

position: "stack" (default) or "dodge"
stroke / strokewidth
strokecolor / strokecolour
direction: :y (default) or :x
dodge_gap
gap

Examples

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

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

# dodge using the group and position arguments
ggplot(df) +
    geom_col(@aes(x = species, y = mean_bill_length_mm, group = sex),
             position="dodge")

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

# color based on grouping variable
ggplot(df) +
    geom_col(@aes(x = species, y = mean_bill_length_mm, color = sex))

source

# TidierPlots.geom_contour — Function.

geom_contour(aes(...), ...)
geom_contour(plot::GGPlot, aes(...), ...)

Represents a grid of data as smooth curves of a surface.

Details

This is geom is equivalent to ggplot2::ggplot(df, aes(x, y, z = density)). Only the x and y aesthetics are required.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Contour)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

NA

Optional Arguments

color / colour
colormap / palette
levels
linewidth
linestyle / linetype

Examples

ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) +
    geom_contour(levels = 10)

source

# TidierPlots.geom_density — Function.

geom_density(aes(...), ...)
geom_density(plot::GGPlot, aes(...), ...)

Represent data as a smooth density curve.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Density)

Required Aesthetics

x

Optional Aesthetics (see aes)

NA

Optional Arguments

color / colour
colormap / palette
strokecolor / strokecolour
strokewidth / stroke
linestyle / linetype
direction=:x
npoints=200

Examples

ggplot(penguins, @aes(x=bill_length_mm)) + geom_density()

ggplot(penguins, @aes(x=bill_length_mm)) +
    geom_density(color = (:red, 0.3), strokecolor = :red, stroke = 2)

source

# TidierPlots.geom_errorbar — Function.

geom_errorbar(aes(...), ...)
geom_errorbar(plot::GGPlot, aes(...), ...)

Represents data as a vertical interval.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Rangebars)

Required Aesthetics

x
ymin
ymax

Optional Aesthetics (see aes)

NA

Optional Arguments

color / colour
direction=:y
linewidth
whiskerwidth / width

Examples

df = DataFrame(
    trt   = [1, 1, 2, 2],
    resp  = [1, 5, 3, 4],
    group = [1, 2, 1, 2],
    lower = [0.8, 4.6, 2.4, 3.6],
    upper = [1.1, 5.3, 3.3, 4.2],
)

ggplot(df, @aes(x = trt, ymin = lower, ymax = upper)) +
    geom_errorbar(width=20, linewidth=2)

source

# TidierPlots.geom_errorbarh — Function.

geom_errorbarh(aes(...), ...)
geom_errorbarh(plot::GGPlot, aes(...), ...)

Represents data as a horizontal interval.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Rangebars)

Required Aesthetics

y
xmin
xmax

Optional Aesthetics (see aes)

NA

Optional Arguments

color / colour
direction=:x
linewidth
whiskerwidth / width

Examples

df = DataFrame(
    trt   = [1, 1, 2, 2],
    resp  = [1, 5, 3, 4],
    group = [1, 2, 1, 2],
    lower = [0.8, 4.6, 2.4, 3.6],
    upper = [1.1, 5.3, 3.3, 4.2],
)

ggplot(df, @aes(y = trt, xmin = lower, xmax = upper)) +
    geom_errorbarh(width=20, linewidth=2)

source

# TidierPlots.geom_histogram — Function.

geom_histogram(aes(...), ...)
geom_histogram(plot::GGPlot, aes(...), ...)

Represents data as a histogram.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Hist)

Required Aesthetics

x

Optional Aesthetics (see aes)

NA

Optional Arguments

bins
normalization
color / colour
stroke / strokewidth
strokecolor / strokecolour

Examples

ggplot(penguins, @aes(x = bill_length_mm)) +
    geom_histogram()

ggplot(penguins, @aes(x = bill_length_mm)) +
    geom_histogram(normalization=:probability, bins=20)

source

# TidierPlots.geom_hline — Function.

geom_hline(aes(...), ...)
geom_hline(plot::GGPlot, aes(...), ...)

Plot a horizontal line at the given y-intercept(s).

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.HLines)

Required Aesthetics

NA

Optional Aesthetics (see aes)

yintercept(s)
color / colour

Optional Arguments

yintercept(s)
color / colour
linewidth
linestyle / linetype
colormap / palette
alpha

Examples

# Plot only a single y-intercept
ggplot() + geom_hline(yintercept = 3)

# Plot multiple y-intercepts
ggplot() + geom_hline(yintercept = [-1, 4])

# Plot multiple y-intercepts mapped to a column
df = DataFrame(y = rand(4))
ggplot(df, @aes(yintercept = y)) + geom_hline()

source

# TidierPlots.geom_label — Function.

geom_label(aes(...), ...)
geom_label(plot::GGPlot, aes(...), ...)

Plot text on a graph.

ggplot2 deviation

Currently this method is the same as geom_text, and does not put the text in a rectangle like in ggplot2.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Text)

Required Aesthetics

x
y
text

Optional Aesthetics (see aes)

color / colour

Optional Arguments

color / colour
colormap / palette
align: tuple of positions (e.g. (:left, :bottom))
font
justification
rotation
fontsize
strokewidth
strokecolor
glowwidth / glow
glowcolor / glowcolour
word_wrap_width
alpha

Examples

df = DataFrame(
    x = [1,1,2,2],
    y = [1,2,1,2],
    t = ["A", "B", "C", "D"]
)

ggplot(df, @aes(x=x, y=y, text=t, color=t)) + geom_label()

ggplot(df, @aes(x=x, y=y, text=t, color=t)) +
    geom_label(fontsize=24, align=(:left, :bottom), font=:bold) +
    geom_point() +
    lims(x = (0, 3), y = (0, 3))

source

# TidierPlots.geom_line — Function.

geom_line(aes(...), ...)
geom_line(plot::GGPlot, aes(...), ...)

Represents data as connected points in the order of the variable on the x-axis.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Lines)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

color / colour

Optional Arguments

color / colour
colormap / palette
linestyle / linetype
linewidth
alpha

Examples

xs = range(0, 2pi, length=30)
df = DataFrame(x = xs, y = sin.(xs))

ggplot(df, @aes(x = x, y = y)) + geom_line()

source

# TidierPlots.geom_path — Function.

geom_path(aes(...), ...)
geom_path(plot::GGPlot, aes(...), ...)

Represents data as connected points in the order in which they appear in the data.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Lines)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

color / colour

Optional Arguments

color / colour
colormap / palette
linestyle / linetype
linewidth
alpha

Examples

ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) +
    geom_path()

source

# TidierPlots.geom_point — Function.

geom_point(aes(...), ...)
geom_point(plot::GGPlot, aes(...), ...)

Represents data as pairs of (x, y) points.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Scatter)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

color / color

Optional Arguments

color / colour
colormap / palette
marker / shape
markersize / size
strokewidth / stroke
strokecolor / strokecolour
glowwidth / glow
glowcolor / glowcolour
alpha

Examples

ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) + geom_point()

ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) +
    geom_point(@aes(color = sex), size=20, stroke=1, alpha=0.6)

source

# TidierPlots.geom_smooth — Method.

geom_smooth(aes(...), ...)
geom_smooth(plot::GGPlot, aes(...), ...)

Represent data as a smoothed or linear fit.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Lines)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

NA

Optional Arguments

method: either "smooth" (default, loess fit) or "lm" (linear fit)
color / colour
linewidth
alpha
linestyle / linetype

Examples

xs = range(0, 2pi, length=30)
ys = sin.(xs) .+ randn(length(xs)) * 0.5
df = DataFrame(x = xs, y = ys)

ggplot(df, @aes(x = x, y = y)) + geom_smooth() + geom_point()

ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) +
    geom_smooth(color=:red, linewidth=10, alpha=0.5)

source

# TidierPlots.geom_step — Function.

geom_step(aes(...), ...)
geom_step(plot::GGPlot, aes(...), ...)

Represents data as a stairstep plot.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Stairs)

Required Aesthetics

x
y

Optional Aesthetics (see aes)

color / colour

Optional Arguments

color / colour
colormap / palette
linestyle / linetype
linewidth
alpha

Examples

xs = range(0, 2pi, length=30)
df = DataFrame(x = xs, y = sin.(xs))

ggplot(df, @aes(x = x, y = y)) + geom_step()

source

# TidierPlots.geom_text — Function.

geom_text(aes(...), ...)
geom_text(plot::GGPlot, aes(...), ...)

Plot text on a graph.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Text)

Required Aesthetics

x
y
text

Optional Aesthetics (see aes)

color / colour

Optional Arguments

color / colour
colormap / palette
align: tuple of positions (e.g. (:left, :bottom))
font
justification
rotation
fontsize
strokewidth
strokecolor
glowwidth / glow
glowcolor / glowcolour
word_wrap_width
alpha

Examples

df = DataFrame(
    x = [1,1,2,2],
    y = [1,2,1,2],
    t = ["A", "B", "C", "D"]
)

ggplot(df, @aes(x=x, y=y, text=t, color=t)) + geom_text()

ggplot(df, @aes(x=x, y=y, text=t, color=t)) +
    geom_text(fontsize=24, align=(:left, :bottom), font=:bold) +
    geom_point() +
    lims(x = (0, 3), y = (0, 3))

source

# TidierPlots.geom_tile — Function.

geom_tile(aes(...), ...)
geom_tile(plot::GGPlot, aes(...), ...)

Plots a heatmap as a collection of rectangles.

Details

x, y, and z must all be the same length, and there must be no duplicate (x, y) pairs. You can think of x, y, and z as triples of the form (x, y, f(x, y)).

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Heatmap)

Required Aesthetics

x
y
z

Optional Aesthetics (see aes)

NA

Optional Arguments

interpolate=false
colormap / palette
alpha

Examples

function mandelbrot(x, y)
    z = c = x + y*im
    for i in 1:30.0; abs(z) > 2 && return i; z = z^2 + c; end; 0
end

xs = -2:0.001:1
ys = -1.1:0.001:1.1
xys = Iterators.product(xs, ys) |> collect |> vec
zs = map(xy -> mandelbrot(xy[1], xy[2]), xys)

df = DataFrame(
    x = first.(xys),
    y = last.(xys),
    z = zs
)

ggplot(df, @aes(x = x, y = y, z = z)) + geom_tile(colormap = :deep)

source

# TidierPlots.geom_violin — Function.

geom_(aes(...), ...)
geom_(plot::GGPlot, aes(...), ...)

Represents data as a violin plot.

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.Violin)

Required Aesthetics

x (integer or categorical)
y (numeric)

Optional Aesthetics (see aes)

color / colour (used in conjunction with dodge)
dodge

Optional Arguments

orientation=:vertical: orientation of box (:vertical or :horizontal)
width=1
gap=0.2
show_notch=false
nothchwidth=0.5
show_median=true
dodge_gap=0.03

Examples

ggplot(penguins, @aes(x=species, y=bill_length_mm)) +
    geom_violin()

ggplot(penguins, @aes(x=species, y=bill_length_mm)) +
    geom_violin(orientation=:horizontal)

ggplot(penguins, @aes(x=species, y=bill_length_mm, dodge=sex, color=sex)) +
    geom_violin()

source

# TidierPlots.geom_vline — Function.

geom_vline(aes(...), ...)
geom_vline(plot::GGPlot, aes(...), ...)

Plot a horizontal line at the given y-intercept(s).

Arguments

plot::GGPlot (optional): a plot object to add this geom to
aes(...): the names of the columns in the DataFrame that will be used in the mapping
...: options that are not mapped to a column (passed to Makie.VLines)

Required Aesthetics

NA

Optional Aesthetics (see aes)

xintercept(s)
color / colour

Optional Arguments

xintercept(s)
color / colour
linewidth
linestyle / linetype
colormap / palette
alpha

Examples

# Plot only a single x-intercept
ggplot() + geom_vline(xintercept = 3)

# Plot multiple x-intercepts
ggplot() + geom_vline(xintercept = [-1, 4])

# Plot multiple x-intercepts mapped to a column
df = DataFrame(x = rand(4))
ggplot(df, @aes(xintercept = x)) + geom_vline()

source

# TidierPlots.label_bytes — Method.

label_bytes(;units=:si, kwargs...)

Convert numeric values into human-readable strings representing byte sizes.

Arguments

units: Can be :si for SI units (powers of 10), :binary for binary units (powers of 1024), or a specific unit string (e.g., MB, GiB).
kwargs...: Additional keyword arguments passed to label_number.

Examples

labeler = label_bytes(units=:si)
labeler([1024, 2048]) # ["1.02 KB", "2.05 KB"]

source

# TidierPlots.label_currency — Method.

label_currency(;kwargs...)

Convert numeric values into currency strings.

Arguments

kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_currency()
labeler([100, 200.75]) # ["$100", "$200.75"]

source

# TidierPlots.label_date — Method.

label_date(;format="m/d/Y")

Convert Date or DateTime values into formatted strings.

Arguments

format: A date format string.

Examples

labeler = label_date(format="Y-m-d")
labeler([Date(2020, 1, 1)]) # ["2020-1-1"]

source

# TidierPlots.label_log — Method.

label_log(;base=10, kwargs...)

Convert numeric values into logarithmic strings with a specified base.

Arguments

base: The logarithmic base.
kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_log(base=10)
labeler([10, 100]) # ["10^1", "10^2"]

source

# TidierPlots.label_number — Method.

label_number(;precision=2, scale=1, prefix="", suffix="", decimal_mark=".", comma_mark=",", style_positive=:none, style_negative=:hyphen, kwargs...)

Format numeric values as strings with various styling options.

Arguments

precision: Number of decimal places.
scale: Scaling factor applied to the numbers before formatting.
prefix: String to prepend to the number.
suffix: String to append to the number.
decimal_mark: Character to use as the decimal point.
comma_mark: Character to use as the thousands separator.
style_positive: Style for positive numbers (:none, :plus, :space).
style_negative: Style for negative numbers (:hyphen, :parens).
kwargs: Additional keyword arguments passed on to format from Format.jl

Examples

labeler = label_number(precision=0, suffix="kg")
labeler([1500.12, -2000.12]) # ["1,500kg", "-2,000kg"]

source

# TidierPlots.label_ordinal — Method.

label_ordinal(;kwargs...)

Convert numeric values into ordinal strings (e.g., 1st, 2nd, 3rd).

Arguments

kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_ordinal()
labeler([1, 2, 3]) # ["1st", "2nd", "3rd"]

source

# TidierPlots.label_percent — Method.

label_percent(;kwargs...)

Convert numeric values into percentage strings.

Arguments

kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_percent()
labeler([0.1, 0.256]) # ["10%", "25.6%"]

source

# TidierPlots.label_pvalue — Method.

label_pvalue(;precision=2, kwargs...)

Format p-values, handling very small or large values with special notation.

Arguments

precision: Number of decimal places for thresholding small values.
kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_pvalue()
labeler([0.0001, 0.05, 0.9999]) # ["<0.01", "0.05", ">0.99"]

source

# TidierPlots.label_scientific — Method.

label_scientific(;kwargs...)

Convert numeric values into scientific notation strings.

Arguments

kwargs: Additional keyword arguments passed to label_number.

Examples

labeler = label_scientific()
labeler([1000, 2000000]) # ["1e+03", "2e+06"]

source

# TidierPlots.label_wrap — Method.

label_wrap(width)

Wrap text strings to a specified width, breaking at spaces.

Arguments

width: The maximum number of characters in a line before wrapping.

Examples

labeler = label_wrap(10)
labeler(["This is a long sentence."]) # ["This is a
long
sentence."]

source

Reference - Internal functions¤

# TidierPlots.position_facets — Function.

Internal function. Given a list of names and (optionally) some constraints, return the relative position of the facets and their labels.

source