Wrap-up

Introduction to Data Visualization with Julia

Gustavo Vieira Suñe

Data Analyst

Chapter 1: Basics of Plots.jl

Why visualize data?
Plotting with Plots.jl
- Line plots
- Scatter plots
Adding title and axis labels
Multiple variables in a plot

Lines plots of the daily high and low prices for the QQQ fund as a function of time for a period of fifty days. The prices exhibit fluctuations around a positive linear trend.

Chapter 2: Advanced plot types

Advanced plotting with StatsPlots.jl
Histograms, grouped histograms and density plots
Bar chars and grouped bar charts
Box plots and violin plots
Plotting time series
- Dealing with dates
Adding annotations to a plot

A histogram displaying onion and wheat prices with a density plot superimposed showing the probability distribution.

Chapter 3: Mastering customization

Saving visualizations to file
Using themes
Customizing plot attributes
- Line attributes
- Marker attributes
- Axis bounds
- Legend title and position
- Transparency
Layouts
Series recipes

A scatter plot depicting the frequency of respondents' K-Pop listening habits against their age, with large diamond-shaped markers with some transparency.

Chapter 4: Plotting from DataFrames

Using the StatsPlots.jl DataFrame plotting recipe
Creating plotting chains with Chain.jl
Plotting data in more dimensions
- Three-dimensional scatter plots
- Two-dimensional histograms
Layouts and DataFrames
Correlation matrix plots

A two-dimensional histogram displaying the distribution of insurance charges and body mass index.

Next steps

Understanding Data Visualization
Communicating Data Insights
Dashboard Design Concepts
Book recommendation: Interactive Visualization and Plotting with Julia

Congratulations!

Introduction to Data Visualization with Julia