Visualizing Data with Python

Course Description

"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insights obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data.

One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way.

In this course, you will learn how to leverage a software tool to visualize data that will also enable you to extract information, better understand the data, and make more effective decisions.

You can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you get free access to Watson Studio. Start now and take advantage of this platform.

What you will learn

• how to take data that at first glance has little meaning and present that data in a form that makes sense to people.


• how to use some data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium for presenting data.

Pre-Requesities

Python Basics for Data Science
Analyzing Data with Python

Syllabus

Module 1 - Introduction to Visualization Tools

• Introduction to Data Visualization


• Introduction to Matplotlib


• Basic Plotting with Matplotlib


• Dataset on Immigration to Canada


• Line Plots

• Area Plots


• Histograms


• Bar Charts

• Pie Charts


• Box Plots


• Scatter Plots


• Bubble Plots

• Waffle Charts


• Word Clouds


• Seaborn and Regression Plots

•  Introduction to Folium


•  Maps with Markers


•  Choropleth Maps