Learning Objectives

• What is Data Visualisation?
• Why Data Visualisation?
• Real-life examples
• Data Visualisation in Python

What is Data Visualisation?

Data Visualization represents data or information in a graph, chart, or other visual formats.

It communicates the relationships of the data with images.

Why Data Visualisation?

A visual summary of information makes identifying patterns, trends, and outliers easier than looking through thousands of rows on a spreadsheet.

It’s the way the human brain works.

Since data analysis aims to gain insights, data is much more valuable when visualized.

“A picture is worth a thousand words.”

Our eyes are drawn to colors and patterns. We can quickly identify red from blue and a square from a circle. Our culture is visual, including everything from art and advertisements to TV and movies.

Data visualization is another form of visual art that grabs our interest and keeps our eyes on the message.

You’ve been surrounded by Data Visualisations all this while!

Google Map Traffic visualization

The live traffic status in Google Maps is another simple example of what is possible through data visualization to make human life simple and easy. You can see the red color indicating slow traffic area in the city on the map and the blue color indicating fast etc.

Hard Disk Drives Interactive Data Visualization

The blue line, the empty space in the horizontal bar chart, and a pie chart are examples of the consumed and free space in the hard disk.

Hard drives data status in interactive visualization is effective to understand even for a normal user.

And that’s always the target of data visualization to make it so much easier and more relevant for people to understand and make quick decisions.

Geo-Spatial Data Visualization

Geospatial visualizations are one of the earliest forms of information visualization.

Amongst the various types of geospatial visualizations, Heat maps are useful when you have to represent large sets of continuous data on a map using a color spectrum.

This map of India shows the average annual rainfall using different shades of blue. The darker the shade of blue, the higher the rainfall.

Can you think of more such examples?

Data Visualisation in Python

Python offers multiple great graphing libraries packed with many different functionalities. Whether you want to create interactive, live, or highly customized plots, python has an excellent library for you.

To get a little overview, here are a few popular plotting libraries:

• Matplotlib
• Pandas Visualization
• Seaborn
• ggplot
• Plotly
• Bokeh
• Altair