suppress printing of penguins data in docs

Author: rdboyes

docs/examples/UserGuide/gettingstarted.jl

@@ -1,7 +1,7 @@
 using TidierPlots
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # ## `ggplot()`
 # `ggplot()` is the starting point of any plot. It sets up the initial plot with default settings that can be later customized with geoms, scales, theme settings and other specifications. `ggplot` usually used with a data source as an argument, and optionally, a set of aesthetics specified by @aes(). The data source is typically a DataFrame.

docs/examples/geoms/geom_bar.jl

@@ -39,7 +39,7 @@
 using TidierPlots
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # For basic counting, provide only an x aesthetic. The height of each bar will represent the count of observations in each category.
 

docs/examples/geoms/geom_boxplot.jl

@@ -49,7 +49,7 @@
 using TidierPlots
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # Create a basic boxplot showing the distribution of bill length for each species:
 

docs/examples/geoms/geom_col.jl

@@ -46,7 +46,7 @@ using TidierPlots
 using TidierData
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # First, we create a summarized dataset with mean bill length by species and sex:
 

docs/examples/geoms/geom_density.jl

@@ -42,7 +42,7 @@
 using TidierPlots
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # Create a basic density plot showing the distribution of bill length:
 

docs/examples/geoms/geom_errorbars.jl

@@ -42,7 +42,7 @@ using TidierData
 using DataFrames
 using Statistics
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # First, create a summary dataset with means and standard deviations:
 

docs/examples/geoms/geom_hist.jl

@@ -48,7 +48,7 @@
 using TidierPlots
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # Create a basic histogram of bill length:
 

docs/examples/geoms/geom_hvlines.jl

@@ -41,7 +41,7 @@ using TidierPlots
 using TidierData
 using DataFrames
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 # ## Horizontal Lines
 

docs/examples/geoms/geom_lines.jl

@@ -88,7 +88,7 @@ ggplot(df, @aes(x = x, y = y)) +
 
 # `geom_path()` connects points in the order they appear in the data. This is useful for trajectories or paths through 2D space:
 
-penguins = penguins_data()
+penguins = penguins_data();
 
 ggplot(penguins, @aes(x = bill_length_mm, y = bill_depth_mm)) +
     geom_path(alpha = 0.3)

docs/examples/geoms/geom_point.jl

@@ -45,7 +45,7 @@ using RDatasets
 using CategoricalArrays
 using Makie
 
-penguins = penguins_data()
+penguins = penguins_data();
 diamonds = dataset("ggplot2", "diamonds");
 mtcars = dataset("datasets", "mtcars");