Plotting data in DataFrames

Introduction to Data Visualization with Julia

Gustavo Vieira Suñe

Data Analyst

Insurance dataset

insurance DataFrame

Age	Sex	BMI	Children	Smoker	Region	Charges
19	female	27.90	0	yes	southwest	16884.90
18	male	33.77	1	no	southeast	1725.55
28	male	33.00	3	no	southeast	4449.46
...	...	...	...	...	...	...

DataFrames are flexible and efficient for tabular data
- StatsPlots has a recipe to plot data in DataFrames
- Introducing the @df notation!

Extracting arrays from DataFrame

Mean charges by region and smoker status

# Group by region and smoker
grouped = groupby(insurance, [:Region, :Smoker])

# Calculate mean charges
grouped_mean_charges = combine(grouped, :Charges => mean)

Each column gives an array of data
- For example, grouped_mean_charges.Region extracts an array containing the regions as strings.

Plotting data in arrays

# Grouped bar chart
groupedbar(

    # Pass arrays as arguments
    grouped_mean_charges.Region,
    grouped_mean_charges.Charges_mean,
    group=grouped_mean_charges.Smoker,

    color=[:teal :orangered2],
    linewidth=0,
    legend_title="Smoker",
    legend_position=:outertopright)
xlabel!("Region")
ylabel!("Insurance Premium (USD)")

A grouped bar chart displaying the insurance premium charges for each region grouped by smoker status.

Plotting from DataFrames directly

# Plot from DataFrame
@df grouped_mean_charges groupedbar(

    # Pass column names
    :Region,
    :Charges_mean,

    group=:Smoker,

    color=[:teal :orangered2],
    linewidth=0,
    legend_title="Smoker",
    legend_position=:outertopright)
xlabel!("Region")
ylabel!("Insurance Premium (USD)")

A grouped bar chart displaying the insurance premium charges for each region grouped by smoker status.

Side-by-side comparison

# Grouped bar chart
groupedbar(

    # Pass arrays as arguments
    grouped_mean_charges.Region,
    grouped_mean_charges.Charges_mean,
    group=grouped_mean_charges.Smoker,

    color=[:teal :orangered2],
    linewidth=0,
    legend_title="Smoker",
    legend_position=:outertopright)
xlabel!("Region")
ylabel!("Insurance Premium (USD)")

# Plot from DataFrame
@df grouped_mean_charges groupedbar(

    # Pass column names
    :Region,
    :Charges_mean,
    group=:Smoker,

    color=[:teal :orangered2],
    linewidth=0,
    legend_title="Smoker",
    legend_position=:outertopright)
xlabel!("Region")
ylabel!("Insurance Premium (USD)")

Chaining DataFrame commands

From before

# Group by region and smoker
grouped = groupby(insurance, [:Region, :Smoker])
# Calculate mean charges
grouped_mean_charges = combine(grouped, :Charges => mean)

Use chaining instead

using Chain
# Chain groupby and combine
grouped_mean_charges = @chain insurance begin
  groupby([:Region, :Smoker])
  combine(:Charges => mean)
end

Plotting chain

# Plotting chain
@chain insurance begin
    # Manipulate data
    groupby([:Region, :Smoker])
    combine(:Charges => mean)

    # Plot data
    @df groupedbar(:Region,
        :Charges_mean,
        group=:Smoker,
        color=[:teal :orangered2],
        linewidth=0, legend_title="Smoker",
        legend_position=:outertopright)

end
xlabel!("Region")
ylabel!("Insurance Premium (USD)")

A grouped bar chart displaying the insurance premium charges for each region grouped by smoker status.

Let's practice!

Introduction to Data Visualization with Julia