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What you will learn

Understand the core concepts of Data Visualization

Level-up Data Viz skills regardless of the programming language or visualization tool you use

What makes Data Visualization “Beautiful”?

Visualizing quantity of variables, their distributions and relationships

Appropriate charts and plots to use for appropriate data

Choosing colors, scales, fonts and symbols for elegant Data Visualization

Advanced Data Visualization with Python using Plotly, Seaborn and Matplotlib

Description

This course will enhance a student’s understanding of charts, plots and graphs and bring it to a whole new level. Whether a student already knows something about Data Visualizations or not, they will definitely take something away after completing this course.

Although this course uses the Python Programming Language to create data visualizations, any other tool or programming language could be used to apply the principles that have been taught in this course.

– Achieve the main goal of data visualization which is to communicate data or information clearly and effectively to readers.


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– Learn various do’s and don’ts of data visualizations, color scales and plot animation regardless of programming language or visualization tool.

– Visualize amounts, distributions, proportions, associations and time-series data.

– Learn how to visualize data like a pro.

– Make use of 3 different Python plotting libraries including Plotly, Seaborn, Matplotlib.

– Make use of your learnings to create beautiful data visualizations that could be used in print media, reports and social media.

– Master visual storytelling to communicate a message supported by the data.

– Identify trends and make data engaging and easily digestible

– Evoke an emotional response from whoever takes a look at your data visualized through various types of charts and plots.

English
language

Content

Principles of Data Visualization

Introduction and Course Outline
Principles of Beautiful Data Visualization
Elements of Data Representation
Types of Data and Scales

Introduction to Data Visualization in Python

Introduction to Data Visualization in Python
Loading and Visualizing Data in Python
Common Plots and Charts

Position and Color Scales

Linear, Logarithmic and Curved Scales
Qualitative and Sequential Color Scales
Diverging and Accent Color Scales
Data Visualization Best Practices

Visualizing Amounts

Bar Plots Part 1
Bar Plots Part 2
Dot Plots
Bar Plots Part 3
Heatmaps

Visualizing Distributions

Histograms
Density Plots
Box Plots
Violin Plots

Visualizing Proportions

Pie Charts Part 1
Pie Charts Part 2
Side by side bars and Stacked bars
Sankey Diagrams
Tree Maps

Visualizing Associations

Scatterplots
Bubble Charts and Scales & Redundancy
3D Scatterplots
Highlighting in Scatterplots
Pair Plots

Visualizing Time-series Data

Line Graphs
Emphasis Using Trendlines
Visualizing Uncertainty in Trendlines
Animated Charts
Course Summary and Thank You